FeedbackIf you find a bug, or have feedback, put it here. Please no job applications in here, click Apply on the job instead.Thanks for the message! We will get back to you soon.

[Spam check] What is the name of Elon Musk's company going to Mars?

Send feedback
Open Startup
Health InsurancePost a job

find a remote job
work from anywhere

πŸ‘‰ Hiring remotely? Reach 1,000,000+ remote workers on the πŸ† #1 Remote Jobs board

Post a job
Hide this

Remote Health by SafetyWing

Global health insurance for freelancers & remote workers










This job post is closed and the position is probably filled. Please do not apply.
\nAt Atomwise, we invented the first deep learning neural networks for structure-based small molecule drug discovery, and we’re currently deploying it in one of the largest applications of machine learning for life sciences. We work on Alzheimer’s, cancer, diabetes, drug-resistant antibiotics, and other diseases. We’ve partnered with 4 of the top-10 US pharma companies, raised over $50M from top VCs, and have 100+ diverse projects currently running.\n\nYou should think about joining us if you care about enabling the application of machine learning to essential problems. For example, we are not constrained by latency or uptime but by scaling and parallelization. Today we can analyze more than 1 billion molecules per day, but there are about 10^24 synthetically-accessible molecules. Come help us pick up a couple of orders-of-magnitude.\n\nOur team has over 35 Ph.D. scientists who contribute to a collaborative academic-like culture that fosters robust scientific and technical discussion. We strongly believe that data wins over opinions, and aim for as little dogma as possible in our decision making. Our team members have expertise in a wide range of disciplines--from computational chemistry and structural biology to cloud-native best practices--and we regularly have internal seminars open to anyone interested in learning about these topics.\n\nOur Engineering team is small and growing quickly. As a result, there’s plenty of opportunities for career growth and to have a significant impact on our success. \n\nYou will\n\n\n* Have the opportunity to learn and improve how we run machine learning at scale to deliver new drugs.\n\n* Play an essential role in designing and building cloud-based solutions consisting of 500+ CPU and GPU instances in a highly dynamic scaling environment.\n\n* Foster high-quality and adaptable software using engineering and Agile best practices.\n\n* Interact closely with our scientists (your users) to scope, design and implement software to tackle cheminformatic and machine learning problems.\n\n\n\n\nRequired Qualifications\n\n\n* Bachelor’s degree in Computer Science with 4+ years of software engineering experience.\n\n* High proficiency in Python and a compiled language (e.g., C++, golang, Java, etc).\n\n* A record of designing and implementing cloud software using docker containers.\n\n* High proficiency with the Linux command-line environment.\n\n\n\n\nPreferred Qualifications\n\n\n* Experience building and deploying batch computing workloads or microservices onto Kubernetes.\n\n* Experience implementing machine learning architectures in PyTorch or TensorFlow\n\n* Background in Biology or a related field.\n\n\n\n\nCompensation & benefits\n\n\n* Competitive salary, commensurate with experience\n\n* Stock compensation plan – you’ll be an Atomwise co-owner\n\n* Platinum health, dental, and vision benefits\n\n* 401k with 4% match\n\n* Flexible work schedule\n\n* Generous parental leave\n\n* Strong emphasis on collaborative learning and career development\n\n\n\n\nAtomwise is not currently offering visa sponsorships for any position. Please only apply if eligible to work in the U.S.\n\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

See more jobs at Atomwise

# How do you apply?\n\n This job post is older than 30 days and the position is probably filled. Try applying to jobs posted recently instead.