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At 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, safe pesticides, among treatments for 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.
You should think about joining us if you care about enabling the application of machine learning to important problems. For example, we are not constrained by latency or uptime but by scaling and parallelization: today we can analyze 100 million molecules per day, but there are about 10^24 (a trillion trillion) synthetically-accessible molecules. Come help us pick up a couple orders-of-magnitude.
Our team has over 20 PhD scientists which contribute to a laid-back and academic-like atmosphere that encourages robust scientific and technical discussion. We believe strongly that data wins over opinions, and aim for as little dogma as possible in our decision making.
Our Engineering team has four members and is growing quickly. As a result, there’s plenty of opportunities to have a big impact on our success. That team headcount includes the manager who has a technical background and, at the time of this writing, still contributes code.
At 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, safe pesticides, among treatments for 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.
You should think about joining us if you care about enabling the application of machine learning to important problems. For example, we are not constrained by latency or uptime but by scaling and parallelization: today we can analyze 100 million molecules per day, but there are about 10^24 (a trillion trillion) synthetically-accessible molecules. Come help us pick up a couple orders-of-magnitude.
Our team has over 20 PhD scientists which contribute to a laid-back and academic-like atmosphere that encourages robust scientific and technical discussion. We believe strongly that data wins over opinions, and aim for as little dogma as possible in our decision making.
Our Engineering team has four members and is growing quickly. As a result, there’s plenty of opportunities to have a big impact on our success. That team headcount includes the manager who has a technical background and, at the time of this writing, still contributes code.
You will
- Help us scale the software and infrastructure running our deep learning technology.
- Be a key player in designing and building cloud-based infrastructure-as-code solutions to support our machine learning workflow (1000+ CPU and GPU instances).
- Work closely with other software engineers via code reviews and testing to foster high-quality code and systems.
- Have the opportunity to expand your skills and experience deeper into software engineering or deeper into systems engineering, with strong mentorship either way.
Required Qualifications
- Bachelor’s degree in Computer Science with 5+ years of software engineering experience, and 3+ years with Python.
- Proficiency with Dockerization of workloads and with configuring container orchestration (e.g. Kubernetes, Mesos, AWS ECS, Docker Swarm).
- Experience writing infrastructure-as-code in Ansible or Terraform.
- Familiarity with the Linux command-line environment and Linux systems administration.
Preferred Qualifications
- Experience writing software based on cloud technologies such as AWS ECS, AWS SQS, AWS Batch, or equivalent.
Compensation & benefits
- Competitive salary, commensurate with experience
- Stock compensation plan – you’ll be an Atomwise co-owner
- Platinum health, dental, and vision benefits
- 401k with 4% match
- Flexible work schedule
- Generous parental leave
- Relaxed work environment
- Strong emphasis on collaborative learning, with a regular schedule of cheminformatics and machine learning seminars
- Great colleagues
Atomwise is not currently offering visa sponsorships for any position. Please only apply if eligible to work in the U.S.
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