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Machine Learning Research Engineer

Profluent

Emeryville, CAJob$200–330K/yrPosted 3mo agoVerified open 3 days ago

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At a glance

Compensation
$200–330K/yr
Location
Emeryville, CA
Work Authorization
US work authorization required

Requirements

Credentials this posting asks for.

Bachelor's degree

Job overview

Profluent is hiring a Machine Learning Research Engineer. Profluent, an AI‑first protein design company in Emeryville, seeks an experienced Machine Learning Engineer to build and improve large‑scale generative models and the supporting infrastructure, enabling scientists to accelerate protein design with robust, scalable pipelines.

Key focus areas include Build robust, reproducible, user‑friendly pipelines for automated model fine‑tuning, alignment and evaluation, Design and implement modular, easy‑to‑maintain, multi‑model pipelines for protein design, and Develop highly scalable ETL pipelines to process petabyte‑scale protein data for model pretraining.

Successful candidates bring BS Or MS In Computer Science, Machine Learning, Or Related Field, 3+ Years Hands-On Experience Building And Training ML Models In PyTorch, and Legal Authorization To Work In The United States. Important skills include Automated Model Fine-Tuning, Model Alignment, Model Evaluation, Multi-Model Pipelines, ETL, and Model Training Optimization. Preferred (not required): Protein Language Models, Bioinformatics, GPU-Level Optimization, and CUDA.

Skills & qualifications

RequiredNice to have

Skills

Automated Model Fine-TuningModel AlignmentModel EvaluationMulti-Model PipelinesETLModel Training OptimizationInference Code OptimizationSoftware DevelopmentInfrastructure DevelopmentPrototyping Research IdeasBringing Ideas to ProductionOwnershipIndependent WorkHigh StandardsFocus on Highest-Impact WorkModel QualityModel EfficiencyModel ReliabilityPythonSoftware Engineering FundamentalsTestingCode QualityVersion ControlML Model Inference OptimizationTransformer-Based ArchitecturesCloud InfrastructureContainerizationGCPAWSAzureKubernetesDockerMachine Learning FundamentalsStatisticsLinear AlgebraProtein Language ModelsBioinformaticsGPU-Level OptimizationCUDATritonDistributed TrainingDDPFSDPMulti-Node GPU ClustersDatabasesData Processing PipelinesOrchestrating Multi-Step ML WorkflowsBuilding Backend SystemsServing ML Models in ProductionOpen Source ML Projects Contributions

Qualifications

BS or MS in Computer Science, Machine Learning, or Related Field3+ Years Hands-on Experience Building and Training ML Models in PyTorchLegal Authorization to Work in the United States

Benefits

Medical Insurance
Dental Insurance
Vision Insurance
Paid Time Off
401(k) Match

Full job description

Profluent is the frontier AI lab for biology. Profluent builds powerful foundation models for all of life's molecules, unlocking solutions that transform medicine, agriculture, and beyond. Founded in 2022 and headquartered in Emeryville, CA, Profluent is backed by leading investors including Altimeter Capital, Bezos Expeditions, Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures and has raised over $150M to date.

We're looking for an experienced Machine Learning Engineer to build and improve the models and ML systems that drive our protein design efforts. In this role, you'll deploy and optimize large-scale generative models for protein design, and develop the surrounding infrastructure and tooling that enable our ML and protein design scientists to work faster and more confidently. As an early member of a small, fast-moving engineering team, you'll have significant ownership over our ML stack and the opportunity to shape how our platform evolves.

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 Who You Are

  • You're comfortable taking ownership and working independently in a fast-moving environment

  • You're an execution-oriented engineer who maintains high standards, and focuses on the highest-impact work

  • You're comfortable owning the full stack of your work, from training code to the infrastructure it runs on

  • You care deeply about model quality, efficiency, and reliability

  • You're willing to step beyond your core responsibilities when the team needs it Representative Projects

  • Building hyperparameter search frameworks for SFT and Alignment workflows

  • Increasing protein language model throughput during long context generation

  • Updating existing model architectures to work and run efficiently on new GPU hardware

  • Implementing a protein design pipeline that integrates prompt retrieval, sequence generation, attribute prediction, and structure prediction

  • Establishing an ETL pipeline for sampling and tokenizing training datasets from an internal database of billions of sequences

  • Developing a benchmarking and evaluation system for newly trained sequence generation models

  • Contributing to the development of an internal service that provides transparent multi-node job submission for ML scientists 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 Preferences

  • Familiarity with protein language models or computational biology

  • Experience with GPU-level optimization (CUDA, Triton)

  • Experience with distributed training (DDP, FSDP, multi-node GPU clusters)

  • Experience with databases and data processing pipelines

  • Experience orchestrating multi-step ML workflows

  • Experience building backend systems that serve ML models in production

  • Contributions to open source ML projects or published research 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.

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 $200,000 — $330,000 USD

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