Senior ML Research Engineer — Bioinformatics & Omics

Outpost Bio; Cambridge (MA); Hybrid; USD 150,000 - 230,000; Full time

Benefits offered by this job

Stock options

Full medical, dental & vision from day

401(k) with match

25 days PTO + birthday off

Remote work up to two weeks per year

Home office stipend

Conference costs covered

Job summary

Outpost Bio in Cambridge, MA is seeking a Senior ML Research Engineer to design and train models for multi-omic data (metagenomics, metabolomics, 16S) and build reproducible training and inference systems. You will own research questions end-to-end, define evaluation standards, and communicate findings through publications and ML conferences.

The role blends biology, data science, and software engineering in a fast-moving lab environment with collaboration across cross-functional teams.

Qualifications

• PhD, publications, or equivalent evidence of independent work.
• Fluency in PyTorch, TensorFlow or another DL framework.
• Experience with Python and software engineering best practices.
• Ability to communicate with biologists and cross-functional teams.

Responsibilities

• Design and train novel machine-learning models for messy multi-omic data.
• Own research questions end to end from hypothesis to write-up.
• Set rigorous evaluation standards, accounting for batch effects, leakage, and correlated samples.
• Turn research into reproducible infrastructure with versioned pipelines and experiment tracking.
• Collaborate across data and lab teams to communicate findings through publications and presentations.

Skills

Collaborative teamwork

Education

PhD in a relevant field

Tools

Python

PyTorch

TensorFlow

Job description

Outpost Bio in Cambridge, MA is seeking a Senior ML Research Engineer to design and train models for multi-omic data (metagenomics, metabolomics, 16S) and build reproducible training and inference systems. You will own research questions end-to-end, define evaluation standards, and communicate findings through publications and ML conferences.

The role blends biology, data science, and software engineering in a fast-moving lab environment with collaboration across cross-functional teams.