Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

MLOps Engineer

Revoco
Bristol
6 days ago
Create job alert

Job Title: MLOps Engineer

Location: Bristol – 1-day onsite p/m

Start Date: ASAP

Salary: £75,000 - £90,000

Note: Candidates must be willing and eligible to undergo SC Clearance.


Join a European leader in AI-driven technology, delivering innovative surveillance solutions that enhance safety and save lives. They provide cutting-edge services combining real-time intelligence, data, and AI to transform operational outcomes globally.


About the Role

We are seeking an MLOps Engineer to manage and optimise the machine learning lifecycle, from development to deployment and monitoring. You will work closely with data scientists, software engineers, and IT teams to ensure seamless, scalable, and reliable machine learning solutions in production environments.


Key Responsibilities

- Pipeline Development: Build and maintain scalable ML pipelines automating training, testing, deployment, and monitoring.

- Model Deployment: Collaborate with data scientists to deploy ML models securely and reliably.

- CI/CD Integration: Maintain CI/CD processes for ML models with version control.

- Infrastructure Management: Set up and manage cloud-based and on-prem ML infrastructure.

- Monitoring & Maintenance: Ensure high availability and performance of deployed models with automated monitoring, logging, and alerting.

- Collaboration: Work with cross-functional teams to deliver solutions that meet technical and business requirements.

- Security & Governance: Implement best practices for data security, model governance, and compliance.

- Documentation & Innovation: Maintain clear documentation and stay updated on MLOps trends and technologies.


Profile & Requirements

- Bachelor’s or Master’s in Computer Science, Data Science, Engineering, or related field.

- 3+ years in ML, DevOps, or MLOps with hands-on experience deploying ML products.

- Python, Go, Rust, or similar programming languages

- ML/DL frameworks (TensorFlow, PyTorch, scikit-learn, etc.)

- DevOps practices, CI/CD, IaC, Docker, Kubernetes

- Version control (Git) and collaborative development tools

- Data engineering and ETL workflows

- Monitoring/logging tools (Prometheus, Grafana, ELK, etc.)

- Cloud platforms (AWS, Azure, Google Cloud) with focus on Google Cloud

- Strong analytical, problem-solving, communication, and collaboration skills; attention to detail; ability to thrive in fast-paced environments.


What We Offer

- Opportunity to work on impactful, high-tech projects with the latest AI & ML technologies.

- Flexible work arrangements and collaborative, inclusive culture.

- Professional development and exposure to cutting-edge tools, including Edge AI and Swarming technologies.

- Competitive salary reflecting experience and expertise.

Related Jobs

View all jobs

MLOps Engineer

MLOPs Engineer

MLOps Engineer

MLOps Engineer

MLOPs Engineer

MLOps Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.