onsite
Applied AI / Machine Learning Engineer
ML Engineer
Design and deploy AI-powered backend services, fine‑tuning deep‑learning models and building robust APIs to deliver intelligent features at scale.
About the role
Key Responsibilities
- Develop, train, and fine‑tune deep‑learning models for computer vision, NLP, or recommendation tasks.
- Design and implement high‑performance RESTful or gRPC APIs that expose model inference services.
- Integrate models into production back‑end systems, ensuring low latency and high reliability.
- Containerize AI services using Docker and orchestrate deployments for scalability.
- Collaborate with data engineers and product teams to define data pipelines, evaluation metrics, and monitoring strategies.
Requirements
- Strong proficiency in Python and experience with TensorFlow or PyTorch.
- Hands‑on experience building and deploying deep‑learning models in production.
- Solid understanding of API design, micro‑services architecture, and containerization (Docker).
- Familiarity with version control (Git) and CI/CD workflows for AI services.
- Ability to troubleshoot performance bottlenecks and optimize model inference.
Skills
pythontensorflowpytorchdeep learningdocker