Senior Machine Learning Engineer

Elsevier; Bradford; On-site; GBP 60,000 - 80,000; Full time

Job summary

A leading academic publishing company in Bradford is seeking a Senior Machine Learning Engineer to develop APIs and scalable pipelines for automated AI product evaluation. The successful candidate will collaborate with product and engineering teams to ensure reliable evaluations. This role requires strong Python and SQL skills, along with experience in cloud platforms and production ML pipelines.

Qualifications

• Master's + 3 years or Bachelor's + 5 years of experience.
• Experience in building production ML pipelines.
• Ability to explain technical details to non-technical stakeholders.

Responsibilities

• Build and maintain evaluation APIs and backend services.
• Develop scalable Python/SQL pipelines.
• Ensure reproducibility and observability across workflows.
• Collaborate with Data Scientists and Engineering teams.
• Support auto-assessments for evaluations.

Skills

Python (FastAPI/Flask)

SQL

Cloud platforms (AWS/Azure/Databricks)

Orchestration frameworks (Airflow, Prefect, Dagster)

Containerization (Docker/K8s)

CI/CD pipelines

Logging and monitoring

Education

Master's in Computer Science, Data Engineering or related field

Bachelor's in Computer Science, Data Engineering or related field

Job description

Introduction

Do you enjoy building robust APIs and scalable pipelines to operationalize model evaluation?
Do you want to help product teams get fast, reliable feedback on their AI outputs through automation?

About our Team

Elsevier's AI Evaluation team designs, builds, and operates NLP/LLM evaluation solutions used across multiple product lines. We partner with Product, Technology, Domain SMEs, and Governance to ensure our AI features are safe, effective, and continuously improving.

About the Role

As a Senior Machine Learning Engineer, you will build and maintain the infrastructure and APIs that power automated evaluation of AI products. You’ll ensure evaluations are scalable, reliable, and integrated into product development workflows, enabling product teams to quickly assess model outputs and iterate on their features.

Responsibilities

• API & platform development — Build and maintain evaluation APIs and backend services to run automated assessments.
• Pipeline orchestration — Develop scalable Python/SQL pipelines, integrate with CI/CD, and implement monitoring/logging for evaluation jobs.
• Infrastructure & reliability — Ensure reproducibility, version control, observability, and error handling across evaluation workflows.
• Collaboration — Work closely with fellow Data Scientists, SMEs, Product, and Engineering teams to operationalize metrics and evaluation processes.
• Automation & tooling — Support auto‑assessments as first‑pass evaluation and integration with downstream SME‑evals.

Requirements

• Education/Experience: Master’s + 3 years, or Bachelor’s + 5 years, in CS, Data Engineering, Software Engineering, or related field; experience building production ML pipelines.
• Technical: Strong Python (FastAPI/Flask), SQL, cloud platforms (AWS /Azure / Databricks); orchestration frameworks (Airflow, Prefect, Dagster); containerization (Docker/K8s); CI/CD pipelines; logging and monitoring.
• Practices: Git, reproducibility, documentation; collaborative coding and design review.
• Communication: Ability to explain technical choices and results to non‑technical stakeholders.
• Mindset: Ownership, bias‑for‑action, curiosity, and collaborative problem‑solving.

Nice to have

• Experience with LLM/NLP evaluation pipelines or agentic systems.
• Familiarity with auto‑assessment frameworks and multi‑product evaluation scaling.
• Exposure to healthcare or regulated content domains.

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