Staff Machine Learning Engineer

Skills

About the Role

Baton Corporation is seeking an experienced Staff Machine Learning Engineer to own machine learning projects from problem definition through deployment and iteration. The role emphasizes production recommendation systems, scalable data pipelines, ML infrastructure, low-latency inference, experimentation, and real-time decision-making.

Requirements

• Experienced machine learning engineer with strong foundations in algorithms, data structures, and statistical modeling.
• Production experience building and deploying recommendation systems with measurable impact.
• Familiarity with retrieval, ranking, personalization, embeddings, candidate generation, cold starts, and sparse data.
• Proficiency in Python and TensorFlow or PyTorch, with strong software engineering and model deployment skills.
• Experience building ML infrastructure, data pipelines, model deployment, monitoring, and systems that scale.
• Comfort across the full ML lifecycle from research and experimentation through deployment and maintenance.
• Startup experience and ability to deliver at high pace amid ambiguity and shifting priorities.
• Hands-on, resourceful, high-agency, ownership-driven, and able to lead projects end to end with minimal guidance.
• Strong communication and collaboration skills with technical and non-technical stakeholders.
• Production experience in fraud detection, abuse prevention, or content moderation is advantageous.
• Interest in blockchain, crypto, and SocialFi technologies is a plus.

Responsibilities

• Design, develop, and deploy recommendation models for discovery, personalization, engagement, and retention.
• Build scalable data pipelines and develop features from large datasets.
• Develop and optimize machine learning infrastructure for reliable training and inference.
• Integrate models into the platform for low-latency inference and real-time processing.
• Design experiments, offline evaluations, and A/B tests to measure impact.
• Apply deep learning, natural language processing, and reinforcement learning techniques where appropriate.
• Monitor, optimize, and iterate on deployed models.
• Develop models for fraud detection, abuse prevention, and content moderation.
• Collaborate with engineers and data scientists on high-volume on-chain and user activity data.
• Translate relevant ML research into practical product improvements.

Benefits

• Unmatched ownership and autonomy.
• Exposure to systems operating at the edge of crypto scale.
• Ability to ship quickly and see real-world impact immediately.