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Role Description

This role offers the opportunity to lead cutting-edge AI and machine learning initiatives, working closely with a highly-skilled team of engineers and researchers. You will design, train, and optimize ML models, translating advanced research into scalable, production-ready systems that solve real-world problems. The position involves building robust ML pipelines, running iterative experiments, and collaborating cross-functionally to integrate AI technologies into key products. This is a remote-friendly, high-impact role where innovation, experimentation, and technical rigor are highly valued. You will have the chance to influence AI strategy, contribute to state-of-the-art research, and deliver solutions that directly benefit customers.

• Design, develop, train, and evaluate machine learning models across research and applied AI initiatives.
• Build and maintain robust ML pipelines for data ingestion, feature engineering, model training, and evaluation.
• Run iterative experiments, test hypotheses, and refine models to improve performance and accuracy.
• Collaborate with researchers, engineers, and stakeholders to translate academic advances into production-ready solutions.
• Optimize model performance through fine-tuning, hyperparameter search, and architecture experimentation.
• Document experimental results, track findings, and share learnings with the broader team.
• Stay current with AI/ML research trends and identify opportunities to apply new techniques to product solutions.
• Participate in stand-by, on-call, or off-hours duties during critical research or deployment milestones as needed.

Qualifications

• Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related field (Master’s or PhD preferred).
• 5+ years of experience in industry or research, with deep hands-on expertise training and evaluating ML models, including language models.
• Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
• Experience 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 analytical and problem-solving skills with the ability to iterate quickly without sacrificing rigor.
• Excellent communication skills, capable of presenting experimental results to technical and non-technical stakeholders.
• Ability to work independently and collaboratively in a fast-paced, remote-first environment.

Benefits

• Competitive salary range: $230,000–$275,000, dependent on experience and location.
• Comprehensive health, dental, and vision insurance.
• Short-term disability and life insurance coverage.
• Paid holidays and generous paid time off.
• 401(k) plan and company equity.
• Fertility treatment benefits.
• Eligibility for a discretionary company-wide bonus.
• Remote-first work environment with flexible work arrangements.

Company Description