Software Engineer, Machine Learning Platform
About The Position
Profluent is seeking a Software Engineer for their Machine Learning Platform team. This role will contribute to training capable models quickly and reliably, and building scalable systems around these models to accelerate protein design. The engineer will build systems and tools for scientists to prototype ideas, scale experiments, and evaluate models, as well as build infrastructure and software for the design team, including the inference stack, model APIs, and design pipelines. The ideal candidate has a strong engineering background and product mindset, will own projects from research to deployment, and will have significant ownership in shaping the technical foundation of the engineering organization.
Requirements
- BS, MS, or PhD in computer science or a related field, or equivalent experience.
- 5+ years of experience in backend or full-stack engineering.
- Experience building tools, platforms, or infrastructure for technical users (other engineers, researchers, data scientists, analysts, etc.).
- Experience building high-performance systems.
- A track record of building systems and software that other engineers and users love to use.
- Comfortable taking ownership and working independently in a fast-moving environment.
- Execution-oriented engineer who maintains high standards and focuses on the highest-impact work.
- Comfortable owning the full stack of your work, from system design to implementation to deployment on infrastructure.
- Care deeply about code quality.
- Build systems that emphasize efficiency, scalability, and reliability.
- Willing to step beyond core responsibilities when the team needs it.
- Legal authorization to work in the United States is required.
Nice To Haves
- Experience building research tooling for ML.
- Experience building backend systems that serve ML models in production.
- Experience transitioning research ideas into production.
- Familiarity with ML frameworks such as PyTorch and MLflow.
- Interest in the intersection of biology and AI.
- Contributions to open source projects with strong user communities.
Responsibilities
- Build and maintain the infrastructure that underpins our model training.
- Build and maintain the infrastructure and software that support model inference and protein design.
- Work alongside ML scientists to standardize common research workflows into reusable tooling.
- Work alongside ML scientists to identify opportunities to build tooling that would enable novel research or accelerate existing research.
- Work alongside protein design scientists to translate bespoke processes into reproducible, standardized workflows we can use to speed up protein design projects.
- Identify and implement solutions to optimize our training and inference workloads and reduce compute and storage costs.
- Implement CI/CD, monitoring, and alerting for the services and applications you stand up, and for others across the team where applicable.
- Follow engineering best practices and share these practices across the team.
Benefits
- 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
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Associate degree
