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Staff Machine Learning Engineer, AI Research

Work from home Full-time role Hiring

Description:

  • Design, train, and evaluate machine learning models for research and applied AI initiatives.
  • Run rapid experiments to test hypotheses and identify model improvements.
  • Collaborate with researchers, engineers, development partners, and stakeholders to translate academic advances into production-ready systems.
  • Build and maintain ML pipelines for data ingestion, feature engineering, model training, and evaluation.
  • Optimize model performance through fine-tuning, hyperparameter search, and architecture experimentation.
  • Track experiment results, document findings, and share learnings with the broader team.
  • Stay current with the latest ML and AI research and identify opportunities to apply new methods.
  • Participate in stand-by, on-call, or off-hours support during critical research or deployment milestones.

Requirements:

  • Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field.
  • 5+ years of industry or research experience.
  • Master's degree or PhD is 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 such as MLflow, Weights & Biases, Kubeflow, or similar.
  • Solid understanding of modern NLP, computer vision, and/or reinforcement learning techniques.
  • Ability to move fast without sacrificing rigor, including knowing when to prototype and when to productionize.
  • Excellent communication skills for presenting experimental results to technical and non-technical stakeholders.

Benefits:

  • Salary range of $230,000 to $275,000, depending on geographic location and experience.
  • Comprehensive health, dental, vision, short-term disability, and life insurance coverage.
  • Paid holidays and paid time off.
  • Fertility treatment benefit.
  • 401(k) plan.
  • Equity package.
  • Eligibility for a discretionary company-wide bonus.
  • Remote-first work environment.

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