We’re looking for a Senior Software Engineer to help design, build, and scale Profluent’s data platform. This platform houses data from protein engineering campaigns, including protein designs, experimental results, partner datasets, analytical outputs, and model-ready training data. It enables rapid machine learning, biological discovery, and secure collaboration across internal and external programs.

This role is ideal for an engineer who enjoys building robust data systems: secure ingestion pipelines, well-structured warehouses, reliable data models, access controls, auditability, and infrastructure that makes complex scientific data usable at scale. You will work closely with ML, bioinformatics, and program teams to ensure Profluent’s data is organized, governed, accessible, and protected.

Responsibilities

• Design, build, and maintain scalable data infrastructure for protein engineering campaigns, including ingestion, transformation, validation, storage, and retrieval of large scientific datasets
• Develop secure data pipelines for internal and partner-generated data, with strong attention to access control, data siloing, provenance, auditability, and compliance with data use restrictions
• Own core components of Profluent’s data warehouse and data platform, using Python, GCP, PostgreSQL, BigQuery, and related cloud-native technologies
• Build systems that transform raw experimental, computational, and partner data into structured, reliable, analysis-ready and model-ready datasets
• Establish best practices for data modeling, metadata management, data quality checks, schema evolution, versioning, and documentation
• Collaborate with ML engineers, computational biologists, data scientists, and program stakeholders to understand data requirements and translate them into scalable technical systems
• Improve engineering quality through thoughtful system design, code review, testing, CI/CD, observability, and maintainable development workflows
• Contribute to architectural decisions for how Profluent stores, secures, organizes, and uses data across programs and partnerships

Qualifications

• 5+ years of software engineering, data engineering, or data platform experience
• Strong proficiency in Python and modern software development practices, including git, testing, code review, CI/CD, and production deployment
• Experience designing and operating production data pipelines, data warehouses, and data models at scale
• Hands-on experience with cloud platforms, preferably GCP, and technologies such as BigQuery, PostgreSQL, object storage, workflow orchestration, and containerized services
• Strong understanding of data security, access control, data partitioning or siloing, audit logging, and managing sensitive or restricted datasets
• Experience working with complex, heterogeneous datasets and building systems that make them reliable, discoverable, and usable
• Ability to work independently, make sound technical decisions, and drive projects from ambiguous requirements to production systems
• BS, MS, or PhD in Computer Science, Engineering, Data Science, Bioinformatics, or a related technical field, or equivalent practical experience

Preferences (but not required)

• Experience with scientific, biological, clinical, genomic, laboratory, or high-throughput experimental data
• Experience managing external partner, customer, or restricted-access datasets
• Familiarity with data governance, lineage, metadata systems, schema registries, or data catalogs
• Experience with research data systems, LIMS, ELNs, Benchling, or adjacent scientific platforms
• Background working with ML, data science, computational biology, or cross-disciplinary technical teams
• Interest in learning biology, gene editing, protein design, or machine learning concepts

What We Offer

• 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
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

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.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

We’re looking for a hands-on engineering manager to lead Profluent’s Lab Informatics Platform team. This team builds the systems scientists use to design experiments, track samples, capture assay data, integrate with Benchling and lab automation, and make experimental data usable for analysis and machine learning.

The ideal candidate is both an experienced people manager and a strong technical lead. You’ll formally manage and mentor a small team while remaining deeply involved in architecture, data modeling, database design, and technical execution. You’ll work closely with wet-lab scientists, automation engineers, data scientists, and ML experts to build practical, scientist-facing tools that make complex experimental workflows scalable, traceable, and actionable.

Responsibilities 

• Lead, mentor, and grow a software engineering team focused on lab informatics systems, scientific data infrastructure, and scientist-facing applications
• Architect and deliver the roadmap for systems that support sample tracking, assay data capture, Benchling integration, lab automation, experimental metadata, and analysis workflows
• Design robust data models for protein engineering and gene editing experiments, including constructs, samples, reagents, cell systems, assay results, metadata, and experimental lineage across mammalian and bacterial workflows
• Partner closely with scientists to translate complex laboratory requirements into scalable software solutions that accelerate Profluent’s design-build-test-learn cycle
• Build and maintain backend systems, APIs, databases, data pipelines, and web applications using technologies such as Python, Django, PostgreSQL, BigQuery, GCP, and modern development workflows
• Establish strong engineering practices across architecture, code review, testing, CI/CD, documentation, and agile delivery

Qualifications 

• 7+ years of software engineering experience, including at least 2 years managing or leading engineers
• BS, MS, or PhD in Computer Science, Bioinformatics, Computational Biology, Engineering, or a related field, or equivalent experience
• Strong technical leadership skills, with a track record of architecting and delivering production-quality software systems
• Proficiency with Python, backend development, databases, APIs, and modern software engineering workflows
• Experience building lab informatics systems, scientific data platforms, LIMS/ELN integrations, research software, or scientist-facing applications
• Experience with data modeling and database design for complex scientific, operational, or experimental workflows
• Demonstrated ability to work closely with scientists and translate ambiguous laboratory workflows into reliable software systems

Preferences (but not required)

• Experience with Benchling, lab automation, instrument data ingestion, sample tracking, or high-throughput experimental data
• Experience with data generated from mammalian or bacterial cell systems, gene editing, protein engineering, or related biological workflows
• Frontend web development experience and interest in building intuitive scientist-facing user interfaces

What We Offer

• 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
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

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.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

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. 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. You’ll also mentor team members, promote software engineering best practices, and help shape the future of Profluent’s computational biology capabilities.

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
• Collaborate with machine learning teams to curate data for model training
• Establish best practices for code review, testing, and CI/CD in computational workflows
• Mentor junior scientists and foster a culture of rigor, reproducibility, and innovation

Qualifications

• PhD or MS in Bioinformatics, Computational Biology, Computer Science, or a related quantitative field
• 5+ years of experience analyzing NGS datasets (e.g., amplicon sequencing, high-throughput editing, or screening experiments)
• Strong programming skills in Python (pandas, numpy, biopython, etc.)
• Expertise with workflow orchestration tools (Nextflow, Snakemake) and cloud environments (GCP, AWS)
• Experience with containerization (Docker, Kubernetes) and scalable compute infrastructure
• Deep understanding of Linux, git-based version control, and software engineering best practices
• Proven ability to transform complex sequencing data into actionable biological insights

Preferences (but not required)

• Experience with gene editing technologies (CRISPR, base or prime editing; strongly preferred)
• Familiarity with SQL and data modeling for biological or experimental data
• Experience with LIMS platforms (e.g., Benchling) and lab data integration
• Track record of developing production-quality scientific software or open-source bioinformatics tools

What We Offer

• 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
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

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.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

Our generative models learn the blueprint of life by modeling large-scale evolutionary data, enabling us to engineer and write biology in unprecedented ways. We are seeking a passionate Computational Research Intern to join moonshot projects at the intersection of bioinformatics and machine learning.

This is a rare opportunity to tackle open-ended scientific and engineering challenges with direct potential for high-impact publications and real-world applications in synthetic biology and protein engineering.

Responsibilities

• Design and implement computational approaches to advance cutting-edge research in bioinformatics and machine learning
• Analyze large-scale genomic and protein datasets to uncover new biological insights and capabilities
• Collaborate closely with scientists and engineers across machine learning, protein engineering, and biology teams
• Document and present research findings internally, with the potential to publish in leading journals and conferences

Qualifications 

• Enrolled in a BS, MS, or PhD program in Bioinformatics, Computational Biology, Computer Science, Statistics, or a related quantitative field
• Strong programming skills in Python and familiarity with scientific computing libraries (e.g., NumPy, pandas, Jupyter)
• Experience in one or more of the following: machine learning, large-scale data analysis, genomics, or protein bioinformatics
• Excellent problem-solving skills, scientific curiosity, and ability to work both independently and collaboratively

Internship Details

• Typical duration: 12 weeks, with flexible start dates
• Hybrid: 2 - 3 days on-site per week in our Emeryville, CA headquarters
• Salary: $1,667 per week
• Opportunity to publish your work and make a lasting impact in computational biology and AI-driven protein design

What We Offer

• Work on moonshot projects at the frontier of AI and biology
• Mentorship from leading experts in bioinformatics, machine learning, and synthetic biology
• A dynamic, mission-driven environment with the resources of a fast-growing, well-funded startup
• Competitive internship compensation and benefits