Machine Learning Engineer

Rebel Recruitment Limited

Nottingham, United Kingdom

yesterday

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Shift work

Languages

English

Job location

Remote

Nottingham, United Kingdom

Tech stack

API

Amazon Web Services (AWS)

Computer Vision

Azure

Big Data

Computer Programming

Continuous Integration

Data Governance

Data Structures

Hadoop

Python

Machine Learning

Recommender Systems

TensorFlow

Software Engineering

Workflow Management Systems

Feature Engineering

PyTorch

Spark

Model Validation

Containerization

Scikit Learn

Kubernetes

Information Technology

Machine Learning Operations

Software Version Control

Data Pipelines

Docker

Microservices

Job description

We are seeking a skilled and motivated Machine Learning Engineer to join our growing team in Nottingham. You will be responsible for designing, building, and deploying scalable machine learning models that drive data-driven decision-making across the business. This role bridges the gap between data science and software engineering, turning prototypes into production-ready systems., * Design, develop, and deploy machine learning models and pipelines in production environments

Collaborate with data scientists, software engineers, and stakeholders to translate business requirements into ML solutions
Optimize model performance, scalability, and reliability
Build and maintain data pipelines and feature engineering workflows
Monitor and retrain models to ensure continued performance over time
Implement best practices for version control, testing, and CI/CD in ML systems
Stay up to date with the latest advancements in machine learning and AI technologies

Requirements

Strong programming skills in Python (e.g., TensorFlow, PyTorch, Scikit-learn)
Experience deploying ML models using cloud platforms (AWS, Azure, or GCP)
Solid understanding of machine learning algorithms, data structures, and software engineering principles
Experience with data pipelines, APIs, and microservices architecture
Familiarity with containerization tools such as Docker and orchestration tools like Kubernetes
Strong problem-solving skills and attention to detail, * Experience with big data technologies (e.g., Spark, Hadoop)
Knowledge of MLOps practices and tools (e.g., MLflow, Kubeflow)
Experience working with NLP, computer vision, or recommendation systems
Understanding of data governance and security best practices, * Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field (or equivalent experience)