Machine Learning Engineer at PwC
May no longer be active — verify on the employer site
At a glance
- Company
- PwC
- Location
- United Kingdom
- Work arrangement
- On-site
- Employment type
- Full-time
- Experience
- 2–5 years
- Working hours
- 40 hours
- Visa sponsorship
- Offered, according to the listing
- Posted
- Added to The Stack
✨ The Stack take on this PwC job
- 🏢 PwC has 22 jobs here, 17 with visa sponsorship see all
- 🛂 Skilled Worker visa. Standard minimum salary: £41,700 a year guide
- 💡 No salary shown. Ask PwC if it is above the minimum.
Updated 2026-11-05, from our data and official sources.
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About the role
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.
Responsibilities
Develop and evolve AI benchmarking and experimentation platforms to evaluate emerging models for client engagements. Design end-to-end workflows and build scalable evaluation frameworks to drive evidence-based technical strategies.
Requirements
Requires strong hands-on experience in ML/LLM experimentation and proficiency in Python, including asynchronous programming. Candidates must have experience deploying ML workloads to cloud platforms and a solid understanding of statistics and experimental design.
Key skills
- Machine Learning — in 291 other listings on The Stack
- Large Language Models — in 46 other listings on The Stack
- Python — in 1200 other listings on The Stack
- Asynchronous Programming — in 25 other listings on The Stack
- Cloud Platforms — in 69 other listings on The Stack
- CI/CD — in 630 other listings on The Stack
- Docker — in 464 other listings on The Stack
- Statistics — in 53 other listings on The Stack
- Experimental Design
- Data Engineering
- Deep Learning
- Data Modeling
- Data Pipeline
- Analytical Thinking
- Artificial Intelligence
- Big Data
On The Stack (as of 2026-11-05)
Frequently asked questions about PwC
Is this Machine Learning Engineer role still open?
It was posted on 2026-06-23. Listings more than 30 days old may no longer be active, so check PwC's site before applying.
Does PwC offer visa sponsorship?
This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on PwC's site.
Where is this role located?
The listing gives the location as United Kingdom. It is marked on-site.
What skills does this role ask for?
The listing names: Machine Learning, Large Language Models, Python, Asynchronous Programming, Cloud Platforms, CI/CD, Docker, Statistics, Experimental Design, Data Engineering, Deep Learning, Data Modeling, Data Pipeline, Analytical Thinking, Artificial Intelligence, Big Data.