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

Apply Now

Machine Learning Engineering Manager...

Tbwa Chiat/Day Inc
London
7 months ago
Applications closed

Related Jobs

View all jobs

Engineering Manager, Machine Learning, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000

Machine Learning Engineer Manager

Data Engineering Manager

Lead Machine Learning Engineer (Credit Risk)

Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000

Machine Learning Engineer

1st Floor The Rex Building, 62-64 Queen Street,London, England, EC4R 1EB Location: London, UK (Hybrid) Type:Full-Time Who we are Artefact is a new generation of data serviceprovider, specialising in data-driven consulting and data-drivendigital marketing. We are dedicated to transforming data intobusiness impact across the entire value chain of organisations.With skyrocketing growth, Artefact has established a globalpresence with over 1,500 employees across 23 offices worldwide. Ourdata-driven solutions are designed to meet the specific needs ofour clients, leveraging our deep AI expertise and innovativemethodologies. Our cohesive teams of data scientists, engineers,and consultants are focused on accelerating digital transformation,ensuring tangible results for every client. Role Overview We arelooking for a Machine Learning Manager to support a team of datascientists and ensure the successful delivery of our projects. Theideal candidate will be willing to be hands-on with projects,meaning involvement in model design, coding, and developingend-to-end data solutions, including data preprocessing,visualization, and deploying models into production environments.One of the key components of the role is to supervise junior andsenior data scientists on code and delivery. Therefore, we ask allapplicants to submit an example of code (a repository, a pullrequest, or something similar) to have an estimate of the hands-oncoding ability. This role is crucial in - Driving project successby providing clear direction, solving complex, industry-drivenproblems, and ensuring high-quality results. - Leading technicalproject delivery through hands-on prototyping, design, and coding.- Leading and upskilling a team of data scientists. Keyresponsibilities - Lead and deliver impactful data transformationprojects for clients. - Build strong client relationships,leveraging your technical expertise to drive operationaltransformation. - Participate in international projects withopportunities for business travel. - Ensure successful projectdelivery and communicate these successes across the company. -Foster continuous learning and growth within the data science team.- Provide mentorship, ensuring high work standards and supportingteam well-being. - Demonstrate technical leadership and contributeto institutional knowledge. - Embody Artefact’s values and inspireothers to do the same. Qualifications: Education & experiencerequired Essential skills: - Degree in Computer Science,Engineering, Mathematics, Statistics, or a related field. - Strongprogramming skills in Python. - Experience working with large-scaledatasets and database systems (SQL and NoSQL). - Understanding ofsoftware development lifecycle and agile methodologies. - Provenexperience designing, developing, and deploying machine learningmodels. - Experience with debugging ML models. - Experience withorchestration frameworks (e.g. Airflow, MLFlow, etc). - Experiencedeploying machine learning models to production environments. -Knowledge of MLOps practices and tools for model monitoring andmaintenance. - Familiarity with containerization and orchestrationtools like Docker and Kubernetes. - Hands-on experience with cloudplatforms such as AWS, Google Cloud Platform, or Microsoft Azure. -Demonstrated ability to identify, analyse, and solve complextechnical problems in innovative ways. - Commitment to stayingupdated with the latest advancements in machine learning andrelated technologies. - Professional experience in a consumermarketing context. Why Join Us: - Artefact is the place to be: comeand build the future of marketing. - Progress: every day offers newchallenges and new opportunities to learn. - Culture: join the bestteam you could ever imagine. - Entrepreneurship: you will bejoining a team of driven entrepreneurs. We won’t give up until wemake a huge dent in this industry! What we are looking for: - ADoer: You get things done and inspire your team to do the same. -An Analyst: You love data and believe every decision should bedriven by it. - A Pragmatist: You have a hacker mindset and alwaysfind quick wins. - A Mentor: Your clients and teams naturally seekyour advice. - An Adventurer: You’re an entrepreneur constantlylooking for problems to solve. #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.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

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.