Machine Learning Scientist

The role

You will architect novel generative models to design new proteins that are functional in wet lab assays. You will work in an interdisciplinary team of machine learners, protein engineers and biologists.

What you will do

• Contribute to a careful curation of training and evaluation data.
• Propose and build ML evaluation metrics that align with real world success and company goals.
• Quickly prototype generative models against lead metrics and perform deep analyses of improvements.
• Collaborate in a joint codebase with other research scientists, engineers and protein designers.
• Contribute to the maintenance of compute and ML development infrastructure.
• Plan wet lab testing campaigns and carry out model inference in collaboration with the bio team.
• Learn from wet lab results and feedback data to models.
• Stay on top of the latest developments in ML.
• Gain a strong working understanding of protein and cell biology.
• Participate in knowledge sharing and attend and present at conferences.

Required qualifications

• Strong ML researcher with experience in generative modeling.
• Led or worked on notable machine learning projects documented by contributions to open source libraries, product launches or high impact publications.
• Proven track record of deep expertise in generative modeling.
• Skillful ML developer who writes robust, tested and easy to maintain ML code.
• Experience using version control and code review systems.
• Experience running training and inference on cloud hardware, parallelizing data and models across accelerators.
• Experience building ML data pipelines for the training and evaluation of deep learning models.
• Ability to analyze raw data, construct dataset splits and build pipelines that perform and scale.
• Intricate understanding of how ML libraries interplay with hardware and data.
• Deep knowledge of best principles and tricks in architecting deep learning models.

Nice to have

• Experience in computational biology or protein design.
• Worked on ML-driven projects in biology.
• Natural science background in physics, biology, chemistry or other related fields.

Benefits

• Private health insurance
• Pension/401(K) contributions
• Generous leave policies (including gender neutral parental leave)
• Hybrid working
• Travel opportunities

About the company

latentlabs offers the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.