Machine Learning Engineer

Lorien; Greater London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A leading technology consultancy in the UK is seeking a Machine Learning Engineer to enhance its data science and AI team. The candidate will be instrumental in building robust ML pipelines and systems for various ML applications, including GenAI features. This hybrid role requires 2 days a week on-site work and supports experience in financial services. If you're passionate about ML and have strong Python skills, we encourage you to apply.

Qualifications

• Strong experience with Python and ML libraries.
• Experience in building and monitoring ML pipelines.
• Familiarity with AWS services for ML deployment.

Responsibilities

• Own the model life cycle: data-train-evaluate-package-deploy-monitor.
• Build reproducible pipelines and automated testing for data/ML.
• Implement model monitoring and rollback plans.

Skills

Python (pandas, NumPy, scikit-learn)

Feature engineering

MLOps: experiment tracking (eg, MLflow)

AWS SageMaker

Data pipelines: Spark/SQL

Job description

Machine Learning Engineer

Hybrid Working - UK Wide - 2 Days a Week On Site

Financial Services

Lorien's leading banking client is looking for a Machine Learning Engineer to join the growing data science and AI team.

You’ll play a key role in building and operating robust ML pipelines and serving systems for classic ML and deep learning models, including those that underpin GenAI features.

This role is based UK Wide.

This role will be Via Umbrella.

Working in a Hybrid Model of 2 days a week on site.

Key Responsibilities

• Own the model life cycle: data‑train‑evaluate‑package‑deploy‑monitor.
• Build reproducible pipelines, infra‑as‑code, and automated testing for data/ML.
• Implement model monitoring (latency, accuracy, drift, bias) and rollback plans.
• Collaborate with data engineers and AI engineers on interfaces and SLAs.

Required Skills & Experience

• Python (pandas, NumPy, scikit‑learn; PyTorch/TF a plus).
• Feature engineering, data quality validation, model training and optimisation.
• MLOps: experiment tracking (eg, MLflow), model registry, CI/CD for ML.
• Serving and orchestration: AWS SageMaker, EKS, batch & Real Time inference.
• Data pipelines: Spark/SQL, orchestration (Airflow), monitoring for drift/perf.

Nice to Have

• Cost/performance optimisation on AWS; GPU scheduling; quantisation/distillation.
• Experience working within Financial Services engineering standards and governance.

Guidant, Carbon60, Lorien & SRG - The Impellam Group Portfolio are acting as an Employment Business in relation to this vacancy.