Svitla - Machine Learning/MLOps Engineer

About the Role :

We are seeking an experienced Machine Learning & MLOps Engineer to design, develop, and optimize pipelines and infrastructure that support large-scale ML model development and deployment. The ideal candidate will work across data, ML, and engineering teams to ensure robust data workflows, reliable automation, and scalable, production-grade ML systems.

This role requires strong technical expertise, hands-on development skills in modern C++, and experience working with large multimodal datasets.

Key Responsibilities :

- Develop, automate, and optimize data extraction and labeling pipelines for scalable ML workflows.

- Design, implement, and refine metrics pipelines, and build monitoring dashboards to track perception system performance in production.

- Build and maintain ETL pipelines and ML infrastructure for training, validating, and deploying ML models at scale.

- Develop interfaces and infrastructure to collaborate with third-party data labeling partners.

- Ensure reproducibility, traceability, observability, and reliability of all perception and ML workflows.

- Work closely with cross-functional teams to translate vague or high-level requirements into fully implemented solutions.

- Support integration of ML models into production-grade C++ software systems.

Required Skills & Abilities :

- 5+ years of experience in modern C++ software design and development.

- Strong hands-on experience with large multimodal datasets and dataset curation workflows.

- Proven ability to architect and implement end-to-end ML solutions, including model training, validation, deployment, and monitoring.

- Experience with ML deployment in production environments involving C++ software stacks.

- Experience with ETL pipelines, data workflow frameworks, or cloud-native MLOps tools (e.g., MLflow, Argo Workflows, dashboards).

- Strong analytical, problem-solving, and debugging skills. Excellent communication skills with a collaborative, self-driven approach.

Desirable Skills :

- Experience in robotics, autonomous driving, or perception systems.

- Hands-on experience implementing end-to-end test frameworks, metrics pipelines, and performance dashboards.

- Experience building analytics, visualization, and insight tools for autonomous driving datasets.

- Familiarity with Docker, Kubernetes, and containerized ML deployments..

- Experience in building 3D Visualization tools for LiDAR point cloud data.