Machine Learning Engineer

Machine Learning Engineer focuses on key objective is to develop and deploy robust deep neural networks for robotics, supported by object detection, segmentation, and scene understanding models.

What the role involves

• Key objective is to develop and deploy robust deep neural networks for robotics, supported by object detection, segmentation, and scene understanding models.
• Build scalable pipelines for training, fine‑tuning, inference, and real-time optimization for reliability and performance.
• Maintain data pipelines for collection, ingestion, curation, versioning, and synthetic data generation.
• Work with distributed training systems (multi‑GPU/cloud) and integrate models into robotics pipelines.

Skills and requirements

• PhD in ML/Robotics/Computer Vision or 2-5+ years of applied ML experience.
• Proficiency in Python (required) and C++ (preferred for robotics integration).
• Experience with ML frameworks such as PyTorch (preferred), TensorFlow, or JAX.
• Proven track record building production ML systems, not just research prototypes.

Candidate fit

• technical judgement, safe working habits, careful diagnostics, and practical problem-solving

Additional role context

• Operate reliably in real‑world industrial environments.
• Translate research into clean, production‑grade software that improves system performance and accelerates deployment.