Genesis Therapeutics | South San Francisco, CA | Onsite (Flexible WFH) | Full-time | https://www.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.
- We currently have a small team of excellent software engineers: graduates from Stanford, UC Berkeley, MIT. Previously worked at Facebook, Google, 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
- $4.1m 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:
- Software Engineer: https://jobs.genesistherapeutics.ai/apply/ILdjypU87G/Softwar...
- AI Engineer: https://jobs.genesistherapeutics.ai/apply/NAtx0CsIIL/AI-Engi...
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
Covariant (https://covariant.ai/) | Berkeley, CA (San Francisco Bay Area) | full-time | onsite
Since the first industrial robots were introduced in the 1960s, robots have automated countless dangerous, repetitive tasks, but they've only reached a fraction of their potential. Incapable of thinking on their own, they can only do pre-programmed tasks in tightly-controlled environments -- they can't understand, learn, or adapt. Covariant was founded in 2017 to change this.
Our vision is the Covariant Brain: universal AI that allows robots to see, reason, and act on the world around them. We’re bringing the Covariant Brain to commercial viability, starting with the industries that make, move, and store things in the physical world.
Our work was recently featured in publications from the New York Times (https://nyti.ms/2SkFoUe) and the Wall Street Journal (https://on.wsj.com/2OpujAe), to IEEE Spectrum (http://bit.ly/2Opw3cy)!
We’re always hiring for a variety of roles, but our current priorities are:
- Site Reliability Engineer: http://bit.ly/2OrhpSf
- Infrastructure Engineer: http://bit.ly/36Xgfo1
- Full-Stack Engineer: http://bit.ly/2Sb7AZO
Experience in AI/ML/robotics is not required!
Bringing AI from laboratory research to success in the real world requires a team that represents that world -- a diversity of backgrounds, points of view, and experiences. Our common denominator: ambitious expectations, love of learning, and empathy for those around us. Curious? Read more about our company and our engineering culture! http://bit.ly/37U1rba
Materials Project, Lawrence Berkeley National Laboratory | Web Developer | Berkeley, CA, USA | Onsite | https://materialsproject.org https://lbl.gov
Mission: We are a group of academic researchers who create and curate the Materials Project, the world's leading database of crystalline materials that is freely available for people to query to find materials for applications such as energy, batteries, solar, water splitting, optoelectronics and more. Our user base is growing exponentially (now >120k) and includes a wide range of people, from students who are just encountering materials science for the first time, to academic researchers and industry users. We’re now in the process of building a new frontend for the website to meet some key needs that have arisen as the project has grown, as well as to share some of the latest data we’ve been generating which will require deep thought in how best to make this data accessible and understandable to the broadest possible audience. If this sounds exciting to you, please get in touch. The Materials Project was founded in 2011.
Technologies: This is a good time to start working with us since we're at the early stages of designing our new frontend, and you will have an opportunity to help us shape what that looks like. We've settled on React and TypeScript for our core technologies, and are committed to modern best practices where possible. Due to the large number of Python developers in our team, we will also be making heavy use of the Plotly Dash framework, and extending this using custom React components, so some Python familiarity will also be useful. All the code we write is open source <3 you can find our code at https://github.com/materialsproject
Team: You will be joining a small team of four core developers, along with a larger research group of many postdocs and graduate students here at LBL, and also interacting with our collaborators worldwide.
COVID statement: This is an on-site job, however we are currently working remote and have been given guidance to expect this to continue until the end of September.
The official job ad, further details on how to apply, and our equal employment opportunity statement are all available here: https://lbl.taleo.net/careersection/2/jobdetail.ftl?job=9028...
Kalepa | Senior Backend and Full-Stack Engineers | New York, NY & Remote | Full-time | VISA https://angel.co/company/kalepa
Kalepa is a New York based, VC backed, startup building software to transform and disrupt the $1T commercial insurance market.
Engineers and designers at Kalepa are solving interesting and challenging problems at the intersection of big data pipelines, cutting-edge machine learning models, intuitive frontend apps, and robust infrastructure. You will be working in a small team building technology from the ground up with the latest stack.
One trillion dollars are spent globally each year on commercial insurance. However, the process for estimating the risk associated with a given business across various perils is still reliant on inefficient and inaccurate forms and research. This information asymmetry leads to a broken set of incentives and a poor experience for both businesses and insurers alike. By combining cutting edge data science, enterprise software, and insurance expertise, Kalepa is delivering precision underwriting at scale. Kalepa is turning real-world data into a complete understanding of risk.
Kalepa's team members have worked at Facebook, Google, Amazon, ClassPass, APT (acquired by Mastercard), the Israel Defense Forces, MIT, Berkeley, and UPenn. We are backed by IA Ventures.
https://angel.co/company/kalepa
Contact: paul.monasterio@kalepa.co