Profluent
Lead Bioinformatics Scientist, NGS
Emeryville, California, United States; Hybrid (2-3 days on-site) · Junior
Work authorization required$160k-$230kDetected 30 days ago
PythonCode ReviewGitSQLAWSGCPCloud PlatformsDockerKubernetesCI/CDLinuxMachine LearningPandasNumPySparkAI OrchestrationBioinformaticsCRISPRNGSExperimental Design
About the role
- You'll also mentor team members, promote software engineering best practices, and help shape the future of Profluent's computational biology capabilities.
- Sponsorship will not be provided now or at any time in the future for this position.
- Hiring Salary Range $160,000 - $230,000 USD
Responsibilities
- Lead design and implementation of scalable NGS analysis pipelines supporting gene editing and protein engineering workflows
- Develop clear, intuitive visualizations and reports to communicate sequencing results and biological insights
- Manage cloud-based compute environments and data systems for large-scale datasets
- Partner with biology teams to analyze results, troubleshoot, and optimize experimental design
- Profluent is an AI-first protein design company.
- You'll work at the intersection of computational biology, software engineering, and experimental biology to build scalable systems that extract clear, actionable insights from large-scale sequencing data.
- In this role, you'll architect core bioinformatics infrastructure, define analytical strategy, and collaborate closely with experimental and ML teams to accelerate design-build-test-learn cycles.
Requirements
- 5+ years of experience analyzing NGS datasets (e.g., amplicon sequencing, high-throughput editing, or screening experiments)
- Expertise with workflow orchestration tools (Nextflow, Snakemake) and cloud environments (GCP, AWS)
- Experience with containerization (Docker, Kubernetes) and scalable compute infrastructure
- Proven ability to transform complex sequencing data into actionable biological insights
- Preferences (but not required)
- Familiarity with SQL and data modeling for biological or experimental data
- Experience with LIMS platforms (e.g., Benchling) and lab data integration
- PhD or MS in Bioinformatics, Computational Biology, Computer Science, or a related quantitative field
- Strong programming skills in Python (pandas, numpy, biopython, etc.)
- Deep understanding of Linux, git-based version control, and software engineering best practices
- Experience with gene editing technologies (CRISPR, base or prime editing; strongly preferred)
- Track record of developing production-quality scientific software or open-source bioinformatics tools
- High-growth opportunity with meaningful impact on the future of protein design
- Competitive compensation package with equity participation
- 401(k) with a strong employer match
Nice to have
- Experience with gene editing technologies (CRISPR, base or prime editing
- strongly preferred)
Compensation
- Hiring Salary Range $160,000 - $230,000 USD
Benefits
- Comprehensive benefits including health/dental/vision insurance
- Generous PTO policy and commitment to work-life balance
- Collaborate with machine learning teams to curate data for model training
Company info
- Founded in 2022, we develop deep generative models to design and validate novel, functional proteins to revolutionize biomedicine.
- Based in Emeryville, CA, we are backed by leading investors including Altimeter Capital, Bezos Expeditions, Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures, and have raised over $150M to date.
- We're seeking an experienced computational scientist to lead the design, development, and operation of the NGS analysis platform that powers Profluent's gene editing and protein design programs.
Equal opportunity
- equal opportunity employer promoting diversity and inclusion in the workspace.
Visa & Work Authorization
- Applicants must have ongoing work authorization in the United States that does not require employer sponsorship.
- Sponsorship will not be provided now or at any time in the future for this position.
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This listing is sourced directly from Profluent's careers page and normalized into a canonical job model.