ML Team Lead

Top Remote Talent

Manchester

11 months ago

Applications closed

Related Jobs

View all jobs

Machine Learning Team Lead

Staff Machine Learning Engineer

Data Team Lead (Hybrid) – Lead Data Engineering & Analytics

Data Engineering Team Lead

Data Engineering Team Lead / Lead Data Engineer

Data Engineering Team Lead | Hybrid, Growth & Impact

A software development company is looking for a talented, long-term ML Team Lead. 

The company is a team of experts providing analytical services to healthcare clients. You will join an international team of first class professionals who are passionate to create products that improve quality of medical services. 

We have the highest expectations in the industry regarding your ability to deliver high quality, performant, scalable, clean, and tested software. 

Responsibilities:

Strong analytical skills (good statistics is a must);

• Team Leadership and Development: Lead a small team of 2-4 data scientists focused on solving challenging problems using tabular data with large, feature-rich datasets. Create a collaborative and productive environment, support team members’ technical and professional growth;

• Technical Task Planning and Prioritization: Work with the Product Manager to understand business goals, set task priorities, and manage team resources effectively. Recommend task prioritization strategies to increase product impact and efficiency;

• Technical Oversight and Quality Assurance: Lead the team through all stages of model development, from design to deployment, ensuring best practices in code quality, documentation, and reproducibility. Set clear, repeatable documentation standards to support scalability and knowledge sharing. Implement systems to monitor model performance and keep ML services stable;

• Cross-Functional Collaboration: Work closely with other teams (e.g., Machine Learning Engineers, MLOps, UI) to ensure ML models integrate smoothly with the overall system and align with other technical projects.

Requirements:
• 5+ years in machine learning with hands-on model development experience;
• 2+ years in a technical leadership role;
• Practical experience with Git, Airflow and MLflow (or similar tools);
• Strong Python skills with experience using popular ML libraries and tools (sklearn, CatBoost, optuna, etc);

•Experience with cloud platforms (AWS, GCP, Azure), especially their ML and data engineering services;

• Advanced SQL skills and experience building/managing data pipelines with Airflow or similar tools;
• Understanding of MLOps practices, including CI/CD for ML;
• English level B2 or higher.

Preferred Qualifications (Optional):
• Experience in healthcare or medical insurance projects;
• Experience with Google Cloud Platform (GCP).

Benefits: 

Flexible working hours; 
Remote work; 
Interesting projects to work on; 
Paid vacations.

#Li - remote

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

Industry Insights

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

Feb 3, 2026

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Jan 29, 2026

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

Jan 24, 2026

Education

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.