Build and deploy machine learning models over omics data (e.g. genomics, transcriptomics, proteomics, epigenomics, and multi-omics), capturing biological structure, variability, and experimental context.
Work with major omics and biomedical databases (e.g. gene, protein, pathway, interaction, and expression resources) to integrate heterogeneous biological signals into unified learning pipelines.
Develop and apply foundation models for biological data, including sequence-based, expression-based, and multi-modal models, adapting them to downstream scientific and product use cases.
Design ML systems that populate, enrich, and reason over a biological knowledge graph, connecting entities such as genes, proteins, pathways, phenotypes, diseases, and experimental evidence.
Apply graph-based methods tailored to biology, including graph embeddings, message passing, and network-aware learning, to model molecular interactions and biological systems.
Collaborate with BenchSci’s Science team to ensure models reflect biological constraints, experimental design, and domain nuance, not just statistical patterns.
Power downstream experiences by surfacing insights through semantic search, recommendation, and conversational AI / chat-based scientific assistants.
Improve scalability, robustness, and interpretability of models operating on large, sparse, noisy, and biased omics datasets.
Lead technical decision-making within the ML team, mentor other engineers, and help define best practices for applied ML in biomedical settings.
Own projects end-to-end, from data exploration and model prototyping to production deployment and monitoring.
Continuously improve the performance and scalability of ML models that are at the core of BenchSci’s products
Regularly investigating what technologies will best enable BenchSci to effectively generate use cases
Advocate for code and process improvements across yourteam, and help to define best practices based on personal industry experience and research
Participate in sprint planning, estimation and reviews. Take ownership of deliverables, and work with teammates to ensure high-quality deliverables

Requirements

Bachelor’s degree or higher in Computer Science, Mathematics, Machine Learning, Bioinformatics, or a related field.
Leadership: 2+ years of tech lead experience in a production ML environment.
Hands-on experience working with omics data and omics derived resources, such as genomic sequences, expression matrices, protein data, or biological networks.
Familiarity with omics and biomedical databases (e.g. gene/protein annotations, interaction networks, pathway databases, expression atlases).
Experience with or strong interest in biological foundation models, such as sequence models, embedding models, or multi-modal models applied to molecular or cellular data.
Solid understanding of graph methods in a biological context, including knowledge graphs, molecular interaction networks, or pathway-level representations.
Experience applying NLP or LLM-based techniques to scientific text or integrating text-based evidence with structured biological data.
Strong experience with TensorFlow, PyTorch, and Omics processing libraries.
Comfort working across disciplines, collaborating closely with scientists, engineers, and product teams.
A team player who strives to see teammates succeed together.
A growth mindset, strong ownership mentality, and desire to work on scientifically meaningful problems.
You have a constant desire to grow and develop.

Benefits

A great compensation package that includes BenchSci equity options
A robust vacation policy plus an additional vacation day every year
Company closures for 14 more days throughout the year
Flex time for sick days, personal days, and religious holidays
Comprehensive health and dental benefits
Annual learning & development budget
A one-time home office set-up budget to use upon joining BenchSci
An annual lifestyle spending account allowance
Generous parental leave benefits with a top-up plan or paid time off options
The ability to save for your retirement coupled with a company match!

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningomics databiological datagraph methodsNLPLLM-based techniquesTensorFlowPyTorchbiological knowledge graphfoundation models

Soft Skills

leadershipcollaborationteam playergrowth mindsetownership mentalitymentoringadvocacy for process improvementscommunicationproblem-solvingtechnical decision-making

Certifications

Bachelor’s degree in Computer ScienceBachelor’s degree in MathematicsBachelor’s degree in Machine LearningBachelor’s degree in Bioinformatics