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Senior Machine Learning Engineer - Capgemini
ML Engineer
Senior Machine Learning Engineer driving end‑to‑end development of Generative AI solutions, from research prototyping to production‑grade Borealis AI products, leveraging Python, deep‑learning frameworks, and cloud infrastructure.
About the role
Key Responsibilities
- Design, develop, and deploy cutting‑edge Generative AI models across the full product lifecycle, from research proof‑of‑concepts to scalable production services.
- Collaborate closely with Borealis research scientists and product managers to translate novel algorithms into market‑ready features.
- Implement robust data pipelines, model training workflows, and continuous integration/continuous deployment (CI/CD) processes using cloud platforms such as AWS.
- Optimize model performance, latency, and cost through techniques like quantization, pruning, and distributed training on GPU/TPU clusters.
- Mentor junior engineers, conduct code reviews, and champion best practices in software engineering, reproducibility, and model governance.
Requirements
- 5+ years of professional experience building and shipping machine‑learning products, preferably in Generative AI or large‑language‑model domains.
- Strong proficiency in Python and deep‑learning frameworks such as TensorFlow or PyTorch.
- Hands‑on experience with cloud services (AWS) and containerization tools (Docker, Kubernetes) for scalable model deployment.
- Demonstrated ability to translate research concepts into production‑grade code, including performance tuning and monitoring.
- Excellent problem‑solving skills and the ability to work cross‑functionally in fast‑paced, collaborative environments.
Skills
pythontensorflowpytorchgenerative aiawsdocker