Inference

Inference

Applied Machine Learning Engineer

San Francisco

Sponsorship not specified$220k-$320kDetected 197 days ago
Machine LearningPyTorchData EngineeringData VisualizationNLPLLMsCustomer SupportResearchAdaptability

About the role

  • Your role sits at the intersection of applied research and production engineering.
  • This role reports directly to the founding team.

Responsibilities

  • Lead projects from from data intake through the full training pipeline, including processing, cleaning, and preparing datasets for model training
  • Build and maintain data processing pipelines for aggregating, transforming, and validating training data
  • Create dashboards and visualization tools to display training metrics, data quality, and model performance
  • Develop robust benchmarks and evaluation frameworks that ensure custom models match or exceed frontier performance
  • Build systems to automate portions of the training workflow, reducing manual intervention and improving consistency
  • Collaborate with infrastructure engineers to scale training across our GPU fleet

Requirements

  • 2+ years of experience training AI models using PyTorch
  • Hands-on experience with post-training LLMs using SFT or RL
  • Strong understanding of transformer architectures and how they're trained
  • Experience with LLM-specific training frameworks (e.g., Hugging Face Transformers, DeepSpeed, Axolotl, or similar)
  • Experience training on NVIDIA GPUs
  • Track record of creating benchmarks and evaluations
  • Ability to take research techniques and apply them to production systems

Nice to have

  • Experience with model distillation or knowledge transfer
  • Experience with distributed training at scale
  • Contributions to open-source ML projects
  • You don't need to tick every box.
  • Curiosity and the ability to learn quickly matter more.

Skills

  • Train models using our internal frameworks and iterate based on evaluation results
  • Take research features and ship them into production settings
  • Apply the latest techniques in SFT, RL, and model optimization to improve training quality and efficiency
  • Deeply understand customer use cases to inform training strategies and surface edge cases

Compensation

  • We offer competitive compensation, equity in a high-growth startup, and comprehensive benefits.
  • The base salary range for this role is $220,000 - $320,000, plus equity and benefits, depending on experience.

Company info

  • You will be responsible for building and improving the core ML systems that power our custom model training platform, while also applying these systems directly for customers.

Equal opportunity

  • Inference.net http://Inference.net is an equal opportunity employer. We welcome applicants from all backgrounds and don't discriminate based on race, color, religion, gender, sexual orientation, national origin, genetics, disability, age, or veteran status.
  • If you're excited about building the future of custom AI infrastructure, we'd love to hear from you. Please send your resume and GitHub to amar@inference.net and/or apply here on Ashby.
  • Inference.net http://Inference.net is an equal opportunity employer.
  • We welcome applicants from all backgrounds and don't discriminate based on race, color, religion, gender, sexual orientation, national origin, genetics, disability, age, or veteran status.
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