Senior Machine Learning Engineer - Capgemini

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.