ML Ops Engineering Lead (Remote - UK)

Jobgether; United Kingdom; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

A leading technology recruitment platform is seeking an experienced ML Ops Engineering Lead to drive the development and deployment of machine learning systems in the United Kingdom. This role offers hands-on leadership, shaping the ML lifecycle and leading a team of engineers. Ideal candidates will have proven leadership in ML Ops, strong cloud platform knowledge, and expertise in CI/CD pipelines. Flexible working hours and a comprehensive benefits package are offered.

Benefits

Competitive salary

Flexible working hours

Professional development opportunities

Access to cutting-edge ML tools

Inclusive work culture

Qualifications

• Proven experience in leading ML Ops or data engineering teams.
• Strong knowledge of cloud platforms and container orchestration.
• Expertise in CI/CD pipelines and automated monitoring.

Responsibilities

• Lead design and management of ML infrastructure and pipelines.
• Oversee deployment and scaling of machine learning models.
• Collaborate to ensure best practices in ML operations.

Skills

Leadership in ML Ops

Cloud platforms expertise (AWS, GCP, Azure)

CI/CD pipeline knowledge

Infrastructure as Code (Terraform, Ansible)

ML frameworks (Python, TensorFlow, PyTorch)

API design and microservices

Strong communication skills

Tools

Kubernetes

Docker

Job description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an ML Ops Engineering Lead in United Kingdom.

This role offers a hands‑on leadership opportunity to drive the development, deployment, and operationalization of machine learning systems at scale. You will lead a team of engineers in designing robust, secure, and highly automated ML infrastructure, ensuring seamless integration with business applications. The position combines technical expertise, strategic thinking, and collaboration across multiple teams, including data science, DevOps, and software engineering. You will shape the ML lifecycle from model development to production deployment, implementing CI/CD pipelines, infrastructure as code, and monitoring solutions. The environment is fast‑paced and innovative, allowing you to influence architecture decisions, drive automation, and mentor a team while delivering high‑impact ML solutions.

Accountabilities

• Lead the design, implementation, and management of end‑to‑end ML infrastructure and pipelines.
• Oversee deployment, monitoring, and scaling of machine learning models in production.
• Collaborate with data scientists, software engineers, and DevOps teams to ensure best practices in ML operations.
• Implement automated CI/CD pipelines, infrastructure as code, and testing frameworks for ML systems.
• Define standards for model reproducibility, reliability, and security across the ML lifecycle.
• Mentor and coach engineering teams, promoting collaboration and knowledge sharing.
• Manage stakeholder communication, project planning, and technical documentation.

Qualifications

• Proven experience leading ML Ops or data engineering teams in production environments.
• Strong knowledge of cloud platforms (AWS, GCP, or Azure) and container orchestration (Kubernetes, Docker).
• Expertise in CI/CD pipelines, infrastructure as code (Terraform, Ansible), and automated monitoring.
• Proficiency in ML frameworks and programming languages such as Python, TensorFlow, PyTorch, or similar.
• Experience with API design, microservices architecture, and system integration.
• Strong leadership, project management, and communication skills, with the ability to influence cross‑functional teams.
• Familiarity with generative AI systems, model deployment strategies, and secure ML practices.
• Advantageous: experience with financial services applications or enterprise‑scale ML platforms.

Benefits

• Competitive salary and comprehensive benefits package.
• Flexible working hours with hybrid or remote work options.
• Opportunities to lead and mentor a high‑performing engineering team.
• Access to cutting‑edge ML tools, cloud platforms, and emerging AI technologies.
• Support for professional development, certifications, and continued learning.
• Inclusive and collaborative work culture with global exposure.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI‑driven job matching.

When you apply, your profile goes through our AI‑powered screening process designed to identify top talent efficiently and fairly:
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills‑based, and free of bias — focusing solely on your fit for the role.
Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps, including interviews or additional assessments, are then made by their internal hiring team.

Thank you for your interest!

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