Profluent
Machine Learning Research Engineer
About this role
Profluent, an AI-first protein design company, seeks a Machine Learning Research Engineer to build and optimize large-scale generative models for protein design. You'll develop ML pipelines, infrastructure, and tooling that enable rapid iteration on protein design research while managing the full stack from training code to cloud deployment.
What you'll do
- Build automated pipelines for model fine-tuning, alignment, and evaluation with reproducibility and usability in mind
- Design modular, maintainable multi-model pipelines for protein design workflows
- Develop scalable ETL pipelines to process petabyte-scale protein sequence data for pretraining
- Optimize model training and inference code for throughput and resource efficiency at scale
- Create infrastructure enabling ML scientists to work seamlessly across distributed and multi-cloud environments
- Collaborate with research scientists to prototype and productionize new research ideas
What they're looking for
- PyTorch and deep learning model development (3+ years)
- Python and software engineering best practices (testing, code quality, version control)
- ML model profiling, benchmarking, and optimization
- Transformer architecture implementation and optimization
- Cloud infrastructure and containerization (GCP, AWS, Azure, Kubernetes, Docker)
- Distributed training frameworks (DDP, FSDP, multi-node clusters)
- GPU-level optimization (CUDA, Triton)
- ETL and data pipeline development
Benefits
- Equity participation in a well-funded startup
- 401(k) with strong employer match
- Comprehensive health, dental, and vision insurance
- Generous PTO and work-life balance commitment
- Professional development in cutting-edge AI and biology intersection
- High-impact role shaping the future of protein design
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Profluent
Profluent develops AI-powered protein design and biomolecular engineering solutions, leveraging machine learning and generative modeling to advance biomedical applications. The company is hiring Machine Learning Scientists specializing in reinforcement learning and generative models, as well as Sustaining Engineers to maintain and enhance their automated high-throughput operations infrastructure.
View all jobs at ProfluentLikely interview questions
- Walk us through your experience optimizing model training or inference at scale—what was the bottleneck and how did you address it?
- Describe a time you owned both the training code and infrastructure for an ML project. How did you approach the end-to-end design?