Job Description:
• Design, train, evaluate, and deploy machine learning models for real-time and near–real-time applications.
• Partner with the Senior Cloud Engineer to deploy models within cloud pipelines.
• Collaborate on the design and optimization of data pipelines used for model training, inference, and monitoring.
• Establish metrics for model performance, data drift, and system health.
• Analyze the impact of new features and model changes in production environments.
• Work closely with cloud, perception, and UI engineering teams to integrate ML outputs into customer-facing products.
Requirements:
• 3–6 years of experience building and deploying machine learning models in production environments.
• Strong foundation in supervised and/or unsupervised learning, time-series, or real-time inference use cases.
• Experience supporting low-latency or streaming ML workloads.
• Hands-on experience working in AWS (or similar cloud environments) alongside cloud engineers.
• Comfort interacting with data stored in PostgreSQL, Snowflake, or similar systems.
• Strong proficiency in Python and common ML libraries (e.g., PyTorch, DeepStream, scikit-learn).
• Familiarity with ML lifecycle tooling (experiment tracking, model versioning, CI/CD for ML).
• Intermediate English level (written and spoken).
Benefits: