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Staff Machine Learning Engineer, AI Research

Remote · USA Full-time New today

Job Description:

  • Design, train, and evaluate machine learning models across a range of research and applied AI initiatives
  • Run rapid, iterative experiments to test hypotheses and surface insights that drive model improvements
  • Collaborate closely with researchers and engineers to translate cutting-edge academic advances into practical, production-ready systems
  • Build and maintain robust ML pipelines for data ingestion, feature engineering, model training, and evaluation
  • Optimize model performance through fine-tuning, hyperparameter search, and architecture experimentation
  • Contribute to a culture of rigorous experimentation; tracking results, documenting findings, and sharing learnings with the broader team
  • Stay current with the latest developments in ML and AI research, and proactively identify opportunities to apply them
  • This position may require stand-by, on-call, or off-hours duties during critical research or deployment milestones

Requirements:

  • Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field with 5+ years of industry or research experience (Master's or PhD a plus)
  • Deep hands-on experience training and evaluating ML models, including language models
  • Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow
  • Familiarity with MLOps tooling and infrastructure (e.g., MLflow, Weights & Biases, Kubeflow, or similar)
  • Solid understanding of modern NLP, computer vision, and/or reinforcement learning techniques
  • Strong ability to move fast without sacrificing rigor; you know when to prototype and when to productionize
  • Excellent communication skills with the ability to clearly present experimental results to both technical and non-technical stakeholders.

Benefits:

  • health, dental, vision, short-term disability, and life insurance
  • paid holidays and paid time off
  • fertility treatment benefit
  • 401(k)
  • equity
  • eligibility for a discretionary company-wide bonus

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