Machine Learning Scientist, Life Science Project

Key Skills

Effective communication skills, Machine learning techniques

Job Description

We are a team of scientists and engineers dedicated to creating transformative computational tools for biology. Our moonshot is to accelerate discovery and innovation in the life sciences, with applications in industrial biotechnology and synthetic biology. Our team is developing technologies that redefine what is possible in a rapidly evolving field. If you are excited to make a difference in this space, we’d love to talk with you.

About the role:

We’re looking for a motivated and versatile machine learning scientist who is passionate about using models to solve real world problems and enjoys working with complex, heterogeneous data. You will be working with our team of computational biologists and software engineers to develop machine learning models for cell biology based on cutting-edge data gathered by our own in-house lab. This involves developing and iterating on model prototypes, designing robust benchmarking experiments, and developing and scaling machine learning infrastructure as needed. You will also preprocess and analyze data from our lab team and our external partners to prepare it for modeling. This role requires expertise developing, evaluating, and scaling complex machine learning models for biological applications.

What you should have:

• Masters or Ph.D. in computational biology, computer science, physics/biophysics, chemistry, or other relevant field; or 5+ years equivalent practical experience
• Strong Python coding skills and practices in a team development context
• Experience training neural network models using modern ML frameworks (e.g., PyTorch/Jax)
• Experience working with biological data for machine learning, for example ‘omics or other genotype-phenotype data; knowledge of microbiology and metabolism a plus
• Experience scaling machine learning pipelines in the cloud
• Can understand the broader scientific/business context of a modeling task
• Can summarize modeling results clearly for audiences with different levels of technical expertise
• Honest, open communicator, takes initiative and high agency.

It’d be great if you also had these:

• Startup experience a plus
• Experience with Bayesian optimization a plus
• High speed of execution

The US base salary range for this full-time position is $165,000 - $230,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.