AirPods Pro noise cancellation almost definitely gave me temporary tinnitus after a few months of usage even though I never listened to music that loud. Switched to regular AirPods two years ago and the tinnitus entirely went away.
138 karma · joined August 23, 2017
We’re a hybrid AI + biotech start-up, developing novel deep learning and molecular simulation techniques to predict molecular properties and using them to accelerate the development of new medicines.
We raised a $52M Series A from Andreessen Horowitz + well-respected biotech investors, and have deployed our technology on several internal drug programs as well as multi-target collaborations with Genentech + Lilly ($20M up-front revenue + $670M potential total value), driving discovery progress at a speed rarely seen in the industry. Now we are scaling the team and technology to support many more drug programs in parallel as well as increasingly difficult protein targets.
We currently have a team (https://www.genesistherapeutics.ai/company.html#team) of about 40 people, split 50/50 between our ML / software team and our biochem team of veteran drug hunters in our own wetlab space. Our ML + software engineers are top-notch -- many graduates from MIT, UC Berkeley, Stanford. Previously worked at OpenAI, Google, Facebook, SingleStore, Jane Street, etc.
We're looking for software engineers (no bio or chem experience expected) to help build flexible production systems to integrate our ML models, molecular simulation platform, and molecular generation techniques into our drug programs. This includes helping build individual algorithmic components, iterating on our chemist-facing model deployment pipeline, and leveraging our autoscaling cluster of thousands of GPUs and tens of thousands of CPUs processing billions of molecules / day.
We're also hiring ML research scientists and computational chemists. Here are all of our open roles: https://jobs.lever.co/genesistherapeutics/
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (optionally virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in 2-3 weeks
Tech Stack: python, pytorch, postgres, flask, kubernetes
Please apply on our website, or feel free to reach out via email directly: ben@genesistherapeutics.ai
We’re a hybrid AI + biotech start-up, developing novel deep learning and molecular simulation techniques to predict molecular properties and using them to accelerate the development of new medicines.
We raised a $52M Series A from Andreessen Horowitz + well-respected biotech investors, and have deployed our technology on several internal drug programs as well as multi-target collaborations with Genentech + Lilly ($20M up-front revenue + $670M potential total value), driving discovery progress at a speed rarely seen in the industry. Now we are scaling the team and technology to support many more drug programs in parallel as well as increasingly difficult protein targets.
We currently have a team (https://www.genesistherapeutics.ai/company.html#team) of about 40 people, split 50/50 between our ML / software team and our biochem team of veteran drug hunters in our own wetlab space. Our ML + software engineers are top-notch -- many graduates from MIT, UC Berkeley, Stanford. Previously worked at OpenAI, Google, Facebook, SingleStore, Jane Street, etc.
We're looking for pure software engineers (no bio or chem experience expected) to help build flexible production systems to integrate our ML models, molecular simulation platform, and molecular generation techniques into our drug programs. This includes helping build individual algorithmic components, iterating on our chemist-facing model deployment pipeline, and leveraging our autoscaling cluster of thousands of GPUs and tens of thousands of CPUs processing billions of molecules / day.
We're also hiring ML research scientists and computational chemists. Here are all of our open roles: https://jobs.lever.co/genesistherapeutics/
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (optionally virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in 2-3 weeks
Tech Stack: python, pytorch, postgres, flask, kubernetes
Please apply on our website, or feel free to reach out via email directly: ben@genesistherapeutics.ai
We’re a hybrid AI + biotech start-up, developing novel deep learning and molecular simulation techniques to predict molecular properties and using them to accelerate the development of new medicines.
We raised a $52M Series A from Andreessen Horowitz + well-respected biotech investors, and have deployed our technology on several internal drug programs as well as multi-target collaborations with Genentech + Lilly ($20M up-front revenue + $670M potential total value), driving discovery progress at a speed rarely seen in the industry. Now we are scaling the team and technology to support many more drug programs in parallel as well as increasingly difficult protein targets.
We currently have a team (https://www.genesistherapeutics.ai/company.html#team) of about 40 people, split 50/50 between our ML / software team and our biochem team of veteran drug hunters in our own wetlab space. Our ML + software engineers are top-notch -- many graduates from MIT, UC Berkeley, Stanford. Previously worked at OpenAI, Google, Facebook, SingleStore, Jane Street, etc.
We're looking for pure software engineers (no bio or chem experience expected) to help build flexible production systems to integrate our ML models, molecular simulation platform, and molecular generation techniques into our drug programs. This includes helping build individual algorithmic components, iterating on our chemist-facing model deployment pipeline, and leveraging our autoscaling cluster of thousands of GPUs and tens of thousands of CPUs processing billions of molecules / day.
We're also hiring ML research scientists and computational chemists. Here are all of our open roles: https://jobs.lever.co/genesistherapeutics/
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (optionally virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in a week or two
Tech Stack: python, pytorch, postgres, flask, kubernetes
Please apply on our website, or feel free to reach out via email directly: ben@genesistherapeutics.ai
We’re a hybrid AI + biotech start-up, developing novel deep learning and molecular simulation techniques to predict molecular properties and using them to accelerate the development of new medicines.
We raised a $52M Series A from Andreessen Horowitz + well-respected biotech investors, and have deployed our technology on several internal drug programs as well as multi-target collaborations with Genentech + Lilly ($20M up-front revenue + $670M potential total value), driving discovery progress at a speed rarely seen in the industry. Now we are scaling the team and technology to support many more drug programs in parallel as well as increasingly difficult protein targets.
We currently have a team (https://www.genesistherapeutics.ai/company.html#team) of about 40 people, split 50/50 between our ML / software team and our biochem team of veteran drug hunters in our own wetlab space. Our ML + software engineers are top-notch -- many graduates from MIT, UC Berkeley, Stanford. Previously worked at OpenAI, Google, Facebook, SingleStore, Jane Street, etc.
We're looking for pure software engineers (no bio or chem experience expected) to help build flexible production systems to integrate our ML models, molecular simulation platform, and molecular generation techniques into our drug programs. This includes helping build individual algorithmic components, iterating on our chemist-facing model deployment pipeline, and leveraging our autoscaling cluster of hundreds of GPUs and thousands of CPUs processing billions of molecules / day.
We're also hiring ML research scientists and computational chemists. Here are all of our open roles: https://jobs.lever.co/genesistherapeutics/
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (optionally virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in a week or two
Tech Stack: python, pytorch, postgres, flask, kubernetes
Please apply on our website, or feel free to reach out via email directly: ben@genesistherapeutics.ai
We’re a hybrid AI + biotech start-up, developing novel deep learning and molecular simulation techniques to predict molecular properties and using them to accelerate the development of new medicines.
We raised a $52M Series A from Andreessen Horowitz + well-respected biotech investors, and have deployed our technology on several internal drug programs as well as multi-target collaborations with Genentech + Lilly ($20M up-front revenue + $670M potential total value), driving discovery progress at a speed rarely seen in the industry. Now we are scaling the team and technology to support many more drug programs in parallel as well as increasingly difficult protein targets.
We currently have a team (https://www.genesistherapeutics.ai/company.html#team) of about 40 people, split 50/50 between our ML / software team and our biochem team of veteran drug hunters in our own wetlab space. Our ML + software engineers are top-notch -- many graduates from MIT, UC Berkeley, Stanford. Previously worked at OpenAI, Google, Facebook, SingleStore (FKA MemSQL), Jane Street, etc.
We're looking for pure software engineers (no bio or chem experience expected) to help build flexible production systems to integrate our ML models, molecular simulation platform, and molecular generation techniques into our drug programs. This includes helping build individual algorithmic components, iterating on our chemist-facing model deployment pipeline, and leveraging our autoscaling cluster of hundreds of GPUs and thousands of CPUs processing billions of molecules / day.
We're also hiring ML research scientists and computational chemists. Here are all of our open roles: https://jobs.lever.co/genesistherapeutics/
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (optionally virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in a week or two
Tech Stack: python, pytorch, postgres, flask, docker, kubernetes
Please apply on our website, or feel free to reach out via email directly: ben@genesistherapeutics.ai
We’re a hybrid AI + biotech start-up, developing novel deep learning and molecular simulation techniques to predict molecular properties and using them to accelerate the development of new medicines.
We raised a $52M Series A from Andreessen Horowitz + well-respected biotech investors, and have deployed our technology on several internal drug programs as well as multi-target collaborations with Genentech + Lilly ($20M up-front revenue + $670M potential total value), driving discovery progress at a speed rarely seen in the industry. Now we are scaling the team and technology to support many more drug programs in parallel as well as increasingly difficult protein targets.
We currently have a team (https://www.genesistherapeutics.ai/company.html#team) of about 30 people, split 50/50 between our ML / software team and our biochem team of veteran drug hunters in our own wetlab space. Our ML + software engineers are top-notch -- many graduates from MIT, UC Berkeley, Stanford. Previously worked at OpenAI, Google, Facebook, SingleStore (FKA MemSQL), Jane Street, etc.
We're looking for pure software engineers (no bio or chem experience expected) to help build flexible production systems to integrate our ML models, molecular simulation platform, and molecular generation techniques into our drug programs. This includes helping build individual algorithmic components, iterating on our chemist-facing model deployment pipeline, and leveraging our autoscaling cluster of hundreds of GPUs and thousands of CPUs processing billions of molecules / day.
We're also hiring ML research scientists and computational chemists. Here are all of our open roles: https://jobs.lever.co/genesistherapeutics/
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (optionally virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in a week or two
Tech Stack: python, pytorch, postgres, flask, docker, kubernetes
Please apply on our website, or feel free to reach out via email directly: ben@genesistherapeutics.ai
We’re a hybrid AI + biotech start-up, developing novel deep learning and molecular simulation techniques to predict molecular properties and using them to accelerate the development of new medicines.
We raised a $52M Series A from Andreessen Horowitz + well-respected biotech investors, and have deployed our technology on several internal drug programs as well as multi-target collaborations with Genentech + Lilly ($20M up-front revenue + $670M potential total value), driving discovery progress at a speed rarely seen in the industry. Now we are scaling the team and technology to support many more drug programs in parallel as well as increasingly difficult protein targets.
We currently have a team (https://www.genesistherapeutics.ai/company.html#team) of about 30 people, split 50/50 between our ML / software team and our biochem team of veteran drug hunters in our own wetlab space. Our ML + software engineers are top-notch -- many graduates from MIT, UC Berkeley, Stanford. Previously worked at OpenAI, Google, Facebook, SingleStore (FKA MemSQL), Jane Street, etc.
We're looking for pure software engineers (no bio or chem experience expected) to help build flexible production systems to integrate our ML models, molecular simulation platform, and molecular generation techniques into our drug programs. This includes helping build individual algorithmic components, iterating on our chemist-facing model deployment pipeline, and leveraging our autoscaling cluster of hundreds of GPUs and thousands of CPUs processing billions of molecules / day.
We're also hiring ML research scientists and computational chemists. Here are all of our open roles: https://jobs.lever.co/genesistherapeutics/
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (optionally virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in a week or two
Tech Stack: python, pytorch, postgres, flask, docker, kubernetes
Please apply on our website, or feel free to reach out via email directly: ben@genesistherapeutics.ai
We’re a hybrid AI + biotech start-up, developing novel deep learning and molecular simulation techniques to predict molecular properties and using them to accelerate the development of new medicines.
We raised a $52M Series A from Andreessen Horowitz + well-respected biotech investors, and have deployed our technology on several internal drug programs as well as a multi-target collaboration with Genentech, driving discovery progress at a speed rarely seen in the industry. Now we are scaling the team and technology to support many more drug programs in parallel as well as increasingly difficult protein targets.
We currently have a team (https://www.genesistherapeutics.ai/company.html#team) of about 30 people, split 50/50 between our ML / software team and our biochem team of veteran drug hunters in our own wetlab space. Our ML + software engineers are top-notch -- many graduates from MIT, UC Berkeley, Stanford. Previously worked at OpenAI, Google, Facebook, SingleStore (FKA MemSQL), Jane Street, etc.
We're looking for pure software engineers (no bio or chem experience expected) to help build flexible production systems to integrate our ML models, molecular simulation platform, and molecular generation techniques into our drug programs. This includes helping build individual algorithmic components, iterating on our chemist-facing model deployment pipeline, and leveraging our autoscaling cluster of hundreds of GPUs and thousands of CPUs processing billions of molecules / day.
We're also hiring ML research scientists and computational chemists. Here are all of our open roles: https://jobs.lever.co/genesistherapeutics/
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (optionally virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in a week or two
Tech Stack: python, C++, pytorch, postgres, flask, docker, kubernetes
Please apply on our website, or feel free to reach out via email directly: ben@genesistherapeutics.ai
We’re a hybrid AI + biotech start-up, developing novel deep learning and molecular simulation techniques to predict molecular properties and using them to accelerate the development of new medicines.
We raised a $52M Series A from Andreessen Horowitz + well-respected biotech investors, and have deployed our technology on several internal drug programs as well as a multi-target collaboration with Genentech, driving discovery progress at a speed rarely seen in the industry. Now we are scaling the team and technology to support many more drug programs in parallel as well as increasingly difficult protein targets.
We currently have a team (https://www.genesistherapeutics.ai/company.html) of about 30 people, split 50/50 between our ML / software team and our biochem team of veteran drug hunters in our own wetlab space. Our ML + software engineers are top-notch -- many graduates from MIT, UC Berkeley, Stanford. Previously worked at OpenAI, Google, Facebook, SingleStore (FKA MemSQL), Jane Street, etc.
We're looking for pure software engineers (no bio or chem experience expected) to help build flexible production systems to integrate our ML models, molecular simulation platform, and molecular generation techniques into our drug programs. This includes helping build individual algorithmic components, iterating on our chemist-facing model deployment pipeline, and leveraging our autoscaling cluster of hundreds of GPUs and thousands of CPUs processing billions of molecules / day.
We're also hiring ML research scientists and computational chemists. Here are all of our open roles: https://jobs.lever.co/genesistherapeutics/
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (optionally virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in a week or two
Tech Stack: python, C++, pytorch, postgres, flask, docker, kubernetes
Please apply on our website, or feel free to reach out via email directly: ben@genesistherapeutics.ai
We’re a hybrid AI + biotech start-up, developing novel deep learning and molecular simulation techniques to predict molecular properties and using them to accelerate the development of new medicines.
We raised $52M Series A from Andreessen Horowitz + well-respected biotech investors, and have deployed our technology on several internal drug programs as well as a multi-target collaboration with Genentech, driving discovery progress at a speed rarely seen in the industry. Now we are scaling the team and technology to support many more drug programs in parallel as well as increasingly difficult protein targets.
We currently have a team (https://www.genesistherapeutics.ai/#team) of about 30 people, split 50/50 between our ML / software team and our biochem team of veteran drug hunters in our own wetlab space. Our ML + software engineers are top-notch -- many graduates from MIT, UC Berkeley, Stanford. Previously worked at OpenAI, Google, Facebook, SingleStore (FKA MemSQL), Jane Street, etc.
We're looking for pure software engineers (no bio or chem experience expected) to help build flexible production systems to integrate our ML models, molecular simulation platform, and molecular generation techniques into our drug programs. This includes helping build individual algorithmic components, iterating on our chemist-facing model deployment pipeline, and leveraging our autoscaling cluster of hundreds of GPUs and thousands of CPUs processing billions of molecules / day. See the full job description here: https://jobs.lever.co/genesistherapeutics/e76a97f1-1157-4bb7...
We're also hiring ML research scientists and computational chemists. Here are all of our open roles: https://jobs.lever.co/genesistherapeutics/
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (optionally virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in a week or two
Tech Stack: python, C++, pytorch, postgres, flask, docker, kubernetes
Please apply on our website, or feel free to reach out via email directly: ben@genesistherapeutics.ai
We’re a hybrid AI + biotech start-up, developing novel deep learning and molecular simulation techniques to predict molecular properties and using them to accelerate the development of new medicines.
We raised $52M Series A from Andreessen Horowitz + well-respected biotech investors, and have deployed our technology on several internal drug programs as well as a multi-target collaboration with Genentech, driving discovery progress at a speed rarely seen in the industry. Now we are scaling the team and technology to support many more drug programs in parallel as well as increasingly difficult protein targets.
We currently have a team (https://www.genesistherapeutics.ai/#team) of about 30 people, split 50/50 between our ML / software team and our biochem team of veteran drug hunters in our own wetlab space. Our ML + software engineers are top-notch -- many graduates from MIT, UC Berkeley, Stanford. Previously worked at OpenAI, Google, Facebook, SingleStore (FKA MemSQL), Jane Street, etc.
We're looking for pure software engineers (no bio or chem experience expected) to help build flexible production systems to integrate our ML models, molecular simulation platform, and molecular generation techniques into our drug programs. This includes helping build individual algorithmic components, iterating on our chemist-facing model deployment pipeline, and leveraging our autoscaling cluster of hundreds of GPUs and thousands of CPUs processing billions of molecules / day. See the full job description here: https://jobs.lever.co/genesistherapeutics/e76a97f1-1157-4bb7...
We're also hiring ML research scientists and computational chemists. Here are all of our open roles: https://jobs.lever.co/genesistherapeutics/
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (optionally virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in a week or two
Tech Stack: python, C++, pytorch, postgres, flask, docker, kubernetes
Please apply on our website, or feel free to reach out via email directly: ben@genesistherapeutics.ai
We’re a hybrid AI + biotech start-up, developing novel deep learning and molecular simulation techniques to predict molecular properties and using them to accelerate the development of new medicines.
We raised $52M Series A from Andreessen Horowitz + well-respected biotech investors, and have deployed our technology on several internal drug programs as well as a multi-target collaboration with Genentech, driving discovery progress at a speed rarely seen in the industry. Now we are scaling the team and technology to support many more drug programs in parallel as well as increasingly difficult protein targets.
We currently have a team (https://www.genesistherapeutics.ai/#team) of about 30 people, split 50/50 between our ML / software team and our biochem team of veteran drug hunters in our own wetlab space. Our ML + software engineers are top-notch -- many graduates from MIT, UC Berkeley, Stanford. Previously worked at OpenAI, Google, Facebook, SingleStore (FKA MemSQL), Jane Street, etc.
We're looking for pure software engineers (no bio or chem experience expected) to help build flexible production systems to integrate our ML models, molecular simulation platform, and molecular generation techniques into our drug programs. This includes helping build individual algorithmic components, iterating on our chemist-facing model deployment pipeline, and leveraging our autoscaling cluster of hundreds of GPUs and thousands of CPUs processing billions of molecules / day. See the full job description here: https://jobs.lever.co/genesistherapeutics/e76a97f1-1157-4bb7...
We're also hiring ML research scientists and computational chemists. Here are all of our open roles: https://jobs.lever.co/genesistherapeutics/
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (optionally virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in a week or two
Tech Stack: python, C++, pytorch, postgres, flask, docker, kubernetes
Please apply on our website, or feel free to reach out via email directly: ben@genesistherapeutics.ai
We’re a hybrid AI + biotech start-up, developing novel deep learning and molecular simulation techniques to predict molecular properties and using them to accelerate the development of new medicines.
We raised $52M Series A from Andreessen Horowitz + well-respected biotech investors, and have deployed our technology on several internal drug programs as well as a multi-target collaboration with Genentech, driving discovery progress at a speed rarely seen in the industry. Now we are scaling the team and technology to support many more programs in parallel as well as increasingly difficult protein targets.
We currently have a team (https://www.genesistherapeutics.ai/#team) of about 30 people, split 50/50 between our ML / software team and our biochem team of veteran drug hunters in our own wetlab space. Our ML + software engineers are top-notch -- many graduates from MIT, UC Berkeley, Stanford. Previously worked at OpenAI, Google, Facebook, MemSQL, Jane Street, etc.
We're looking for pure software engineers (no bio or chem experience expected) to help scale our cloud infrastructure and build internal tools for our ML and chemistry teams. We have an autoscaling cluster of hundreds of GPUs and thousands of CPUs processing billions of molecules / day, with a spiky, heterogeneous workload of deep learning training + evaluation as well as molecular simulation. See the full job description here: https://jobs.lever.co/genesistherapeutics/e76a97f1-1157-4bb7...
We're also hiring ML research scientists and computational chemists. Here are all of our open roles: https://jobs.lever.co/genesistherapeutics/
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (optionally virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in a week or two
Tech Stack: python, C++, pytorch, postgres, flask, docker, kubernetes
Please apply on our website, or feel free to reach out via email directly: ben@genesistherapeutics.ai
We’re a hybrid AI + biotech start-up, developing novel graph neural networks to predict molecular properties and using them to accelerate the development of new medicines.
We're looking for a strong infrastructure engineer, who will take over the lead responsibility for scaling our model training infrastructure within Google Cloud Platform as well as developing our own physical colocated cluster.
Also looking for great software engineers and ML researchers with an interest in drug discovery -- no biology or chemistry experience required.
- Recently raised $52M Series A led by Rock Springs Capital, Andreessen Horowitz participating: https://techcrunch.com/2020/12/02/genesis-therapeutics-raise...
- Recently announced a multi-target drug discovery partnership with Genentech: https://www.businesswire.com/news/home/20201019005182/en/Gen...
- We currently have a small team of excellent ML + software engineers: graduates from Stanford, UC Berkeley, MIT. Previously worked at Facebook, Google, Dropbox, Memsql, Jane Street
- In addition to strong software + ML talent, our small team has top drug discovery chemists who have collectively discovered several FDA-approved drugs before
Here are our open roles:
- Lead Infrastructure Engineer: https://jobs.lever.co/genesistherapeutics/cbf4ca99-2afb-4d23...
- AI Engineer (Research Scientist): https://jobs.lever.co/genesistherapeutics/c1b7564f-181b-4e45...
- Software Engineer: https://jobs.lever.co/genesistherapeutics/e76a97f1-1157-4bb7...
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (now virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in a week or two
Tech Stack: python, C++, pytorch, postgres, docker, kubernetes, various computational chemistry libraries + tools
Please apply online, or email me if you have any questions: ben@genesistherapeutics.ai
Also, 1-indexed arrays are a major turn-off.
We’re a hybrid AI + biotech start-up, developing novel neural networks to predict molecular properties and using them to accelerate the development of new medicines.
We're looking for a strong infrastructure engineer, who will take over the lead responsibility for scaling our model training infrastructure within Google Cloud Platform as well as developing our own physical colocated cluster.
Also looking for great software engineers and ML researchers with an interest in drug discovery -- no biology or chemistry experience required.
- Recently raised $52M Series A led by Rock Springs Capital, Andreessen Horowitz participating: https://techcrunch.com/2020/12/02/genesis-therapeutics-raise...
- Recently announced a multi-target drug discovery partnership with Genentech: https://www.businesswire.com/news/home/20201019005182/en/Gen...
- We currently have a small team of excellent ML + software engineers: graduates from Stanford, UC Berkeley, MIT. Previously worked at Facebook, Google, Dropbox, Memsql, Jane Street
- In addition to strong software + ML talent, our small team has top drug discovery chemists who have collectively discovered several FDA-approved drugs before
Here are our open roles:
- Lead Infrastructure Engineer: https://jobs.lever.co/genesistherapeutics/cbf4ca99-2afb-4d23...
- AI Engineer (Research Scientist): https://jobs.lever.co/genesistherapeutics/c1b7564f-181b-4e45...
- Software Engineer: https://jobs.lever.co/genesistherapeutics/e76a97f1-1157-4bb7...
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (now virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in a week or two
Tech Stack: python, C++, pytorch, postgres, docker, kubernetes, various computational chemistry libraries + tools
Please apply online, or email me if you have any questions: ben@genesistherapeutics.ai
High-strength 3D printing however, of composites / metal, has a much higher market ceiling. Can certainly be cost-competitive with CNC and probably also expendable mold casting in the short-term.
We’re a hybrid AI + biotech start-up, developing novel neural networks to predict molecular properties and using them to accelerate the development of new medicines.
Looking for great software engineers and ML researchers with an interest in drug discovery -- no biology or chemistry experience required. We all learn from each other here.
- Recently announced a multi-target drug discovery partnership with Genentech: https://www.businesswire.com/news/home/20201019005182/en/Gen...
- Recently raised $52M Series A led by Rock Springs Capital, Andreessen Horowitz participating: https://www.businesswire.com/news/home/20201202005297/en/Gen...
- We currently have a small team of excellent AI + software engineers: graduates from Stanford, UC Berkeley, MIT. Previously worked at Facebook, Google, Dropbox, Memsql, Jane Street
- Core deep learning tech was invented by co-founder + CEO Evan Feinberg during his PhD at Stanford’s Pande lab (the lab that did Folding@Home). See the peer-reviewed PotentialNet paper: https://pubs.acs.org/doi/10.1021/acscentsci.8b00507
- Our platform was validated in collaboration with a top-five pharma company, in a public paper: https://arxiv.org/abs/1903.11789
- In addition to strong software + AI talent, our small team has top drug discovery chemists who have collectively discovered several FDA-approved drugs before
Here are our open roles:
- AI Engineer (Research Scientist): https://jobs.lever.co/genesistherapeutics/c1b7564f-181b-4e45...
- Infrastructure Engineer: https://jobs.lever.co/genesistherapeutics/cbf4ca99-2afb-4d23...
- Software Engineer: https://jobs.lever.co/genesistherapeutics/e76a97f1-1157-4bb7...
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (now virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in a week or two
Tech Stack: python, C++, pytorch, postgres, docker, kubernetes, various computational chemistry libraries + tools
Please apply online, or email me if you have any questions: ben@genesistherapeutics.ai
We’re a hybrid AI + biotech start-up, developing novel neural networks to predict molecular properties and using them to accelerate the development of new medicines.
Looking for great software engineers and ML researchers with an interest in drug discovery -- no biology or chemistry experience required. We all learn from each other here.
- Just announced a multi-target drug discovery partnership with Genentech: https://www.businesswire.com/news/home/20201019005182/en/Gen...
- We currently have a small team of excellent AI + software engineers: graduates from Stanford, UC Berkeley, MIT. Previously worked at Facebook, Google, Dropbox, Memsql, Jane Street
- Core deep learning tech was invented by co-founder + CEO Evan Feinberg during his PhD at Stanford’s Pande lab (the lab that did Folding@Home). See the peer-reviewed PotentialNet paper: https://pubs.acs.org/doi/10.1021/acscentsci.8b00507
- Seed round led by Andreessen Horowitz, and we currently have lots of runway
- Our platform was validated in collaboration with a top-five pharma company, in a public paper: https://arxiv.org/abs/1903.11789
- In addition to strong software + AI talent, our small team has top drug discovery chemists who have collectively discovered several FDA-approved drugs before
Here are our open roles:
- AI Engineer (Research Scientist): https://jobs.lever.co/genesistherapeutics/c1b7564f-181b-4e45...
- Infrastructure Engineer: https://jobs.lever.co/genesistherapeutics/cbf4ca99-2afb-4d23...
- Software Engineer: https://jobs.lever.co/genesistherapeutics/e76a97f1-1157-4bb7...
Interview process: 1-2 one-hour technical phone screens, 1 day on-site (now virtual) with 3 one-hour technical questions. All these include extra time to chat, answer your questions about Genesis, and meet us. Can go from first email to offer in a week or two
Tech Stack: python, C++, pytorch, postgres, docker, kubernetes, various computational chemistry libraries + tools
Please apply online, or email me your resume: ben@genesistherapeutics.ai
Target ID is hard, but we also have known biologically valid targets that are simply undruggable so far (KRAS is the most obvious example). Solving computational chemistry problems is a much more tractable, high-leverage endeavor. And we can in fact use that progress to accelerate biological research itself — for example, quickly developing bioavailable tool compounds via virtual screen to test biological hypotheses in mice, a rational “pharmacological knockout” approach.
We can reduce the biological space in a smart way, we don’t have to brute force this.
Still, I do have some EQ. A lot of candidates exhibit visible anxiety and then get into a rhythm and calm down when they start coding. Or they visibly calm down once I start asking them questions about how they're thinking and coax them towards viable implementation. On the flip side, a lot of candidates actually exhibit overconfidence running in the wrong direction, which I try to lightly mitigate but can't prevent in all cases without giving an unfair advantage.