Machine Learning Engineer at PwC

on-site · full_time · Visa sponsorship

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Responsibilities:
- Design, build and evolve AI/LLM benchmarking and experimentation platforms to support client engagements.
- Define and run end‑to‑end benchmarking workflows: translate use cases into evaluation plans, run experiments, and produce insights.
- Implement scalable evaluation frameworks, metrics and automated pipelines for repeatable model comparison.
- Develop and maintain robust experimentation infrastructure (containers, CI/CD, cloud deployments) for reliable reproducibility.
- Produce clear, client‑ready reports and support technical demos and deep‑dive sessions with stakeholders.

Requirements:
- Hands‑on experience with ML/LLM experimentation and structured evaluation frameworks.
- Strong Python skills, including asynchronous programming and multithreading; emphasis on maintainable code.
- Experience deploying ML workloads to cloud platforms (Azure, AWS or GCP) and familiarity with CI/CD and containerisation (Docker/Podman).
- Solid understanding of statistics and experimental design and ability to translate results into actionable recommendations.
- Comfortable operating autonomously in fast‑moving workstreams and collaborating across research and delivery teams.
- Good communication skills for presenting technical findings to non‑technical stakeholders.