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

Apply Now

Machine Learning Engineer (Visa Sponsorship Available)

Techwaka
Edinburgh
1 week ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

£60k per annum

As aMachine Learning Engineer, you will be part of an MLOps team, working alongside data scientists, software engineers, and other stakeholders to bring machine learning models to life. You will be responsible for deploying, maintaining, and monitoring models in production, improving model performance, and refining the machine learning infrastructure to support business objectives. Your role will also involve optimizing workflows, integrating CI/CD pipelines, and ensuring the scalability and reliability of AI-driven solutions.

Key Responsibilities:

  • Model Deployment: Collaborate with data scientists to deploy machine learning models, ensuring quality and scalability.
  • Pipeline Development: Build and maintain model pipelines to integrate with existing systems and workflows.
  • CI/CD for ML: Design and implement continuous integration and delivery pipelines for efficient model deployment.
  • Model Monitoring: Monitor machine learning models in production, ensuring ongoing performance and reliability.
  • Collaboration: Work with cross-functional teams to design solutions that align with business objectives and best practices in machine learning.
  • Optimization: Continuously improve machine learning infrastructure and production workflows.
  • Strong technical foundation in machine learning and software engineering
  • Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn)
  • Experience with cloud platforms (AWS, GCP, Azure)
  • Experience with CI/CD pipelines for machine learning (e.g., Vertex AI)
  • Familiarity with data processing tools like Apache Beam/Dataflow
  • Strong understanding of monitoring and maintaining models in production environments
  • Experience with containerization tools (e.g., Docker)
  • Problem-solving skills with the ability to troubleshoot model and pipeline issues
  • Strong communication skills for cross-team collaboration

Requirements

  • Bachelor's degree in Computer Science, Data Science, or a related field
  • 3+ years of experience in deploying and maintaining machine learning models
  • Experience with cloud platforms, model pipelines, and CI/CD processes
  • Strong coding skills in Python

Benefits

  • Flexible Working Options: Including hybrid and remote options
  • Competitive Compensation Package + Bonus
  • 25 Days Holiday Per Year(increasing to 28 after 2 years)
  • 2 Paid Volunteering Days Per Yearfor giving back to causes you care about
  • Learning & Development Opportunities: Access to industry training through learning platforms
  • Pension & Life Insurance
  • Health Cash Plan & Online GPservices
  • Paid Parental Leave
  • Season Ticket Loan & Cycle-to-Work Scheme
  • Discounted Gym Membership
  • Central Office Locationwith complimentary snacks and refreshments
  • Relocation Assistance & Work Visa Sponsorshipfor international talent
  • Employee Assistance Programme (EAP)
  • Company Events: Regular social events, team-building activities, and access to over 4,000 deals and discounts on travel, electronics, fashion, and more.


#J-18808-Ljbffr

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.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.