onsite
Machine Learning Engineer - MaxInsights
ML Engineer
Design and deploy end‑to‑end machine learning pipelines for perception and embodied intelligence, collaborating with researchers and product teams to turn real‑world data into production‑ready deep learning solutions.
About the role
Key Responsibilities
- Develop and maintain scalable ML pipelines covering data ingestion, preprocessing, model training, evaluation, and deployment.
- Implement state‑of‑the‑art deep learning architectures for perception and human‑centric tasks using frameworks such as TensorFlow or PyTorch.
- Collaborate with research scientists to translate experimental models into production‑ready services.
- Containerize and orchestrate ML workloads on cloud platforms (e.g., AWS) using Docker and Kubernetes.
- Monitor model performance in production, conduct root‑cause analysis, and iterate on improvements.
Requirements
- Strong programming skills in Python and experience with deep learning libraries (TensorFlow, PyTorch).
- Hands‑on experience building and deploying ML systems at scale, preferably on AWS.
- Proficiency with containerization (Docker) and orchestration (Kubernetes) for reproducible environments.
- Solid understanding of data engineering concepts, model evaluation metrics, and version control.
- Ability to work in ambiguous problem spaces, communicate effectively across multidisciplinary teams, and deliver production‑grade solutions.
Skills
pythontensorflowpytorchawsdockerkubernetes