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

Apply Now

Machine Learning Engineer, Sr.

ORB Sport
London
9 months ago
Applications closed

Related Jobs

View all jobs

Sr. Machine Learning Engineer

Sr. Machine Learning Engineer, AWS

Machine Learning Engineer, AI Foundations

Sr Data Scientist (London)

Data Scientist | Python | SQL | Statistics | Machine Learning | Hybrid, Oxford

Sr. Data Scientist, GenAI Algorithms (Based in Dubai)

What you’ll be working on

Research, develop, and implement machine learning algorithms for use in software and hardware applications.

Your day-to-day

  1. Leads complex model development projects to introduce advanced machine learning techniques and algorithms, ensuring integration with production systems. Lead problem-solving efforts across projects.
  2. Architects and optimises data infrastructure to support scalable machine learning applications.
  3. Drives strategic decisions in project and product meetings, ensuring alignment of machine learning goals with business objectives.
  4. Spearheads initiatives, piloting and integrating new technologies into the business workflow.
  5. Drives innovation through advanced research projects, leading to patentable technology and publications.
  6. Mentor team members in machine learning and advanced troubleshooting techniques to ensure that best practices are followed.
  7. Executes end-to-end machine learning model development from ideation to deployment. Optimises model performance and scalability.
  8. Builds, deploys, monitors, and continuously optimises ML models and developing automated ML models’ training and inference pipelines.
  9. Develops training and cross-validation data sets for machine learning algorithms.
  10. Translates product management, engineering and business constraints and queries into tractable data science questions.
  11. Designs and maintains robust data pipelines for real-time data processing and analysis.
  12. Leads the troubleshooting of complex data challenges.
  13. Develops frameworks and tools to improve model performance and insights.
  14. Performs other related duties and projects as business needs require at direction of management.

You should apply if

  1. Bachelor’s degree in Computing Science, Data Science, Machine Learning, Applied Mathematics, Statistics, or related field; or any equivalent education and/or experience from which comparable knowledge, skills and abilities have been demonstrated/achieved. Master’s degree preferred.
  2. Minimum seven (7) years of experience in Machine Learning.

Even better if you have

  1. Certification in Machine Learning libraries such as Tensorflow, PyTorch, Scikit-learn, NumPy, and Pandas preferred.

Pay range: Competitive

Hybrid work schedule

#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.