Model Ownership: Design and execute fine-tuning strategies (LoRA, full fine-tuning) and own the experimentation cycle from hypothesis through production deployment.
Data Strategy: Build and refine data collection and labeling strategies for complex, messy domains, including designing auto-labeling pipelines.
Architecture: Evaluate and select base models (proprietary and open-source) for domain-specific tasks, focusing on small language models (SLMs).
Deployment: Deploy fine-tuned models to production using cloud ML platforms (Vertex AI, SageMaker, or equivalent).
Evaluation: Develop rigorous evaluation frameworks that measure real-world performance on agentic workflows, not just benchmarks.

Requirements

5+ years of experience in applied ML with a focus on model training and fine-tuning in a commercial setting.
2+ years of hands-on experience with LoRA and full fine-tuning—you have shipped these, not just read about them.
Track record of deploying fine-tuned models to production on cloud ML platforms.
High comfort level working with messy, unstructured data and designing labeling strategies from scratch.
Proficiency with HuggingFace, PyTorch, and at least one cloud ML platform.
Strong opinions about base model selection, held loosely—you can articulate tradeoffs between architectures.

Benefits

100% fully paid medical, vision, and dental for employees and their dependents
Generous time off; we observe all US federal holidays, close our office for a winter break (12/24-12/31), in addition to granting 18 PTO days and 10 sick days
Outstanding compensation package; competitive commissions for revenue roles and quarterly bonuses for non-revenue positions
A strong commitment to diversity, equity, and inclusion
Eligibility to participate in additional benefits such as 401k match up to 5%, 100% paid life insurance (up to $100,000 coverage), and parental leave
A collaborative and positive culture - your team will be as smart and driven as you
Limitless growth and learning opportunities

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

model trainingfine-tuningdata collectiondata labelingauto-labeling pipelinesevaluation frameworkssmall language modelscloud ML deploymentmessy data handlingarchitecture tradeoffs

Soft Skills

strong opinionsarticulation of tradeoffs