Job Number: 17734

External Description:

Job title - Machine Learning Developer

Location: Warwick

Hybrid: 2 days a week in the office, 3 days a week working from home 

Contract length: 6 months (possible extension) 

Rate: £500 per day - Outside IR35 

Randstad Sourceright, a leading provider of RPO & MSP Recruitment Services is currently recruiting for a Machine Learning Developer to work for a leading global energy technology company. 

 

The Role:

We are seeking an experienced Machine Learning Developer to design, build, deploy, and maintain end-to-end ML solutions that power data-driven decision-making across our digital ecosystem. This role is ideal for someone who thrives at the intersection of applied machine learning, ML Ops engineering, and production-grade software development.

You will work closely with cross-functional teams—including data engineers, software developers, product owners, and project leaders—to transform ambiguous real-world data and business problems into scalable, resilient, and high-impact ML systems.

This is not a research role; we need a "hands-on" engineer who can build, deploy, and operationalize models that drive immediate business value.

You will participate in pair-programming, debug production issues, and translate complex business needs into ML-ready requirements. 

Responsibilities:

 

1. End-to-End Machine Learning Development

• Build and own ML solutions from data ingestion through modelling, evaluation, deployment, and monitoring.
• Develop, train, and evaluate machine learning models using modern ML frameworks and libraries.

2. Production Engineering & MLOps

• Deploy, operationalize, and maintain ML models in production environments, implementing CI/CD pipelines, Docker/containerization, orchestration, automated retraining, and monitoring.
• Write modular, production-ready Python code and reusable ML components.

3. Data Preparation & Feature Engineering

• Extract, clean, transform, and validate datasets from diverse sources to support robust model development.
• Handle ambiguity in real-world, imperfect data and design reproducible data processing pipelines.

4. Model Quality & Risk Management

• Apply rigorous evaluation practices: cross-validation, bias/variance analysis, overfitting detection, and data leakage prevention.
• Monitor models for drift, performance degradation, and operational issues.

5. Collaboration & Stakeholder Engagement

• Work cross-functionally with engineers, developers, architects, and project teams to align technical solutions with business objectives.
• Clearly communicate findings, risks, solution design, and technical trade-offs to both technical and non-technical stakeholders.

6. Innovation & Modern ML

• Work with emerging approaches such as LLMs, SLMs, embeddings, and prompt-based workflows.
• Stay up to date with current ML engineering, MLOps practices, tooling, and cloud-native capabilities.

 

Key Skills and experience required:

 

• 5+ years of experience designing and implementing end-to-end ML solutions in production.
• Strong command of ML algorithms, model development, training, validation, and optimization.
• Expertise in Python, ML libraries, and version control (Git).
• Clear understanding of model evaluation, data leakage, and the bias/variance trade-off.
• Hands-on experience with cloud platforms (AWS/Azure/GCP) and MLOps practices, including Docker, CI/CD, deployment, and monitoring.
• Demonstrated success deploying and maintaining production ML models and writing modular, production-grade code.
• Strong experience preparing, transforming, and validating complex real-world datasets (in Snowflake or similar cloud data platforms).
• Experience with enterprise system data (SAP, Salesforce, PLM, Teamcenter) is desirable.
• Familiarity with LLMs/SLMs and modern ML frameworks (e.g., PyTorch, TensorFlow, HuggingFace).
• Excellent problem-solving abilities and communication skills.
• Proven ability to work cross-functionally with engineering and product teams.

 

A Snapshot of a Typical Day

 

A typical day for an ML Developer in this role may include:

• Reviewing model performance dashboards to detect drift or anomalies.
• Working with engineers to refine a data pipeline or debug a production model issue.
• Pair-programming with developers to implement new pipeline components or optimize code for production.
• Running experiments on new ML architectures or tuning hyperparameters for an active use case.
• Meeting with project teams to translate business needs into ML-ready requirements, and effectively communicate solution design to build confidence, validate outcomes and drive adoption
• Evaluating risks such as data leakage, insufficient sampling, data imbalance, or other data quality issues and proposing mitigations.
• Exploring and testing improvements using LLM-based workflows or modern ML tooling.
• This role offers the opportunity to make meaningful impact by delivering scalable, stable, and business-critical intelligent systems.

 

 

 

RSR supports applications from a diverse talent pool. We welcome the opportunity to discuss flexibility requirements. If you require any reasonable adjustments to be made to enable you to participate in the recruitment process, please contact us on the below or -

If this isn’t the role you’re looking for right now, please visit our contractor portal below where you will see all of our live roles and communities to join:   

http://contractortalent.workgr8.io/ 

 

Job Number: SEFGJP00028305

Community / Marketing Title: Machine Learning Developer

Location_formattedLocationLong: Warwick, West Midlands GB