Job Title: Machine Learning Software Engineer
Location: South San Francisco, CA – open for REMOTE
Duration: 12 months
Computational technologies are increasingly a core part of drug discovery and development. We are on a mission to leverage big data, massive computing power, as well as advanced AI algorithms to provide far more therapies at far less cost to society.
Client’s Early Clinical Development (ECD) department is seeking Machine Learning Engineers reporting to the head of AI and Cloud Engineering. The AI & Cloud Engineering (ACE) group breaks new ground in applying advanced AI methods including Deep Neural Network to clinical datasets to support clinical decisions, operational decisions, patient response and safety prediction, and personalized medicine clinical development.
The Machine Learning Engineer will primarily be responsible for the machine-learning pipeline including training, validation, and deployment state of the art machine learning models on large-scale datasets in collaboration with AI scientists and other collaborators.
Have a very ownership-driven culture. We provide and expect ownership, freedom, and responsibility of all team members.
Are solution-focused. Solving the underlying problem is more valuable than writing lots of code.
Have a good sense of humor.
Want to make a positive difference in society.
- MS or PhD in computer science or engineering or a related field.
- Solid experience in writing clean, efficient, and sustainable code in Python.
- Experience working in a team to solve analytical problems using quantitative approaches.
- Hands-on experience with data modeling and analysis.
- Demonstrated ability to design, implement, and scale machine learning workflows; including deployment and delivery of production-ready model APIs.
- Demonstrated proficiency with version control systems and automated software testing and delivery.
- Experience with AI/Client frameworks such as TensorFlow or PyTorch.
- Proficiency with containerized workflows and architectures.
- 3+ years of professional experience within the full software development lifecycle from planning through deployment and maintenance
- Able to present your work, both verbally and in writing, to diverse audiences including scientists, technical colleagues, and management
- Experience with AWS services is recommended
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