AI/ML Engineer

About This RoleAI processing…

Key ResponsibilitiesTypical for this role

• 1
  Drive day-to-day execution of the work outlined in this role
• 2
  Collaborate with cross-functional partners to deliver outcomes
• 3
  Communicate progress, blockers, and decisions clearly
• 4
  Continuously improve how the team operates

Requirements

• Experience building and deploying deep learning models in production, with a solid grasp of architecture choice, training dynamics, and evaluation — and the judgment to model design choices
• Solid machine learning fundamentals: classical modeling, evaluation design, and knowing which metric actually answers the question in front of you
• Hands-on experience across the end-to-end ML lifecycle — training, experimentation, optimization, deployment, and monitoring
• Comfort with messy real-world data, including label definition, leakage, class imbalance, and train/serve skew
• Strong proficiency in Python and SQL, with deep learning frameworks such as PyTorch and distributed compute such as Spark or PySpark
• Working knowledge of modern ML infrastructure — AWS and tools such as SageMaker, Airflow, Kafka, Redis, and Snowflake — and an MLOps mindset for keeping production systems healthy
• The ability to operate independently in ambiguous environments, and to communicate clearly with both technical and non-technical partners

Perks & Benefits