Senior ML Engineer for Protein Design Platform

Profluent; Emeryville (CA); Hybrid; USD 200,000 - 330,000; Full time

Benefits offered by this job

Equity participation

401(k) match

Generous PTO

Professional development

Job summary

Profluent in Emeryville, CA (hybrid 2-3 days on-site) is seeking an experienced Machine Learning Engineer to build and optimize ML systems for protein design, deploying large-scale generative models and enabling researchers.

As an early member of a small team, you will own the ML stack, pipelines for training and inference, ETL for petabyte-scale data, and production readiness. The role requires 3+ years PyTorch experience, strong Python, and cloud/containerization know-how.

Qualifications

• BS or MS in Computer Science, Machine Learning, or a related field.
• 3+ years of hands-on experience building and training ML models in PyTorch.
• Strong Python and software engineering fundamentals, including testing, code quality, and version control.
• Experience profiling, benchmarking, and optimizing ML model training and inference.
• Experience implementing or optimizing transformer-based architectures.
• Familiarity with cloud infrastructure and containerization (GCP, AWS, Azure, Kubernetes, Docker).
• Strong fundamentals in ML, statistics, and/or linear algebra.

Responsibilities

• Build robust, reproducible and user-friendly pipelines for automated model fine-tuning, alignment and evaluation.
• Design and implement modular, easy-to-maintain, multi-model pipelines for protein design.
• Develop highly scalable ETL pipelines to process petabyte-scale protein data for model pretraining.
• Optimize model training and inference code to maximize throughput and resource utilization when deployed at scale.
• Develop software and infrastructure that enable the ML team to work quickly and frictionlessly in distributed and multi-cloud environments.
• Partner with ML and protein design scientists to prototype research ideas and bring them into production.

Skills

PyTorch ML models

Python & software engineering

Model training & inference

Transformer architectures

Cloud & containers

ML foundations

Education

BS/MS in Computer Science or ML

Tools

GCP

AWS

Azure

Kubernetes

Docker

Job description

Profluent in Emeryville, CA (hybrid 2-3 days on-site) is seeking an experienced Machine Learning Engineer to build and optimize ML systems for protein design, deploying large-scale generative models and enabling researchers.

As an early member of a small team, you will own the ML stack, pipelines for training and inference, ETL for petabyte-scale data, and production readiness. The role requires 3+ years PyTorch experience, strong Python, and cloud/containerization know-how.