ML Platform / MLOps Engineer
Profluent is an AI-first protein design company. 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.
As we continue to push the boundaries of what is possible, we’re seeking an ML Platform / MLOps Engineer on the machine learning team to build and operate the infrastructure that powers our machine learning systems. You will work closely with machine learning scientists and engineers to develop reliable, scalable platforms for training, evaluating, and deploying large-scale generative biology models.
As an early member of the company, you’ll have significant ownership over the systems and tools that enable our research team to move quickly from experiments to production models.
What You'll Work On
- Infrastructure supporting large-scale generative models for proteins
- Systems that process massive biological datasets
- Experimentation platforms that enable rapid iteration by ML researchers
- Production services powered by machine learning models
Responsibilities
- Develop infrastructure that enables researchers to run large-scale ML training and inference workloads reliably and efficiently on GPU clusters
- Implement and maintain security best practices across our ML infrastructure, including access control, secrets management, and least-privilege policies
- Monitor and optimize infrastructure performance, reliability, and cost
- Build and maintain machine learning pipelines to support model inference workloads
- Implement CI/CD pipelines for machine learning models and services
- Develop tooling that helps researchers move quickly from experiments to production models
- Maintain infrastructure for model serving and internal APIs
Qualifications
- BS in Computer Science or a related field
- 3+ years of experience building or operating production ML systems
- Experience with MLOps, ML infrastructure, or ML platform engineering
- Strong experience with cloud infrastructure (GCP preferred)
- Experience working with containerized workloads and orchestration systems (Kubernetes, Docker)
- Experience building data or ML pipelines
- Familiarity with CI/CD and infrastructure-as-code practices
Preferences (but not required)
- Experienced with the challenges of working with large scale ML models
- Experience with transitioning research ideas into production
- Familiarity with ML frameworks such as PyTorch, MLFlow
- Interested in the intersection between biology and AI
What we offer at Profluent
- A high-growth opportunity with meaningful impact
- Competitive compensation package
- Health insurance (health/dental/vision)
- Generous paid time off (PTO) policy
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.
Hiring Salary Range
$180,000 - $250,000 USD
Create a Job Alert
Interested in building your career at Profluent? Get future opportunities sent straight to your email.
Apply for this job
*
indicates a required field
