Senior/Principal AI Engineer (AI Framework).

Medtronic
London
9 months ago
Applications closed

Related Jobs

View all jobs

Principal Data Scientist - NLP

Principal Data Scientist - Marketing

▷ (Urgent Search) Senior Principal Data Scientist,NLP

Senior Data Engineer

Senior Software Engineer (GO/PHP)

Data Engineering Lead

Careers that Change Lives 
Acquired by Medtronic – the world’s largest medical device company – in 2019, Digital Technologies is a part of the Surgical Robotics operating unit. The company was founded by two surgeons to realize the mission of bringing safe and standardized surgical care to patients around the world.

As a Principal Artificial Intelligence Engineer, focused in developing an AI framework, you will help to design, implement, and maintain our internal AI development library and tool ecosystem. You will become part of a talented team exploring new concepts through fast iterative prototyping. You will collaborate as an AI software expert with our other machine learning engineers, platform engineers and research experts of the team.

A Day in the Life 
In our computer vision/machine learning team, you will be responsible for: 
• Building and maintaining our common code base for the development of AI models 
• Re-designing, improving and/or optimizing the way AI models are built and data is stored/managed during training 
• Working closely to the team to optimize training cycles so that we can make the most of our HW infrastructure 
• Accelerating model development by delivering high quality and easy to use tools 
• Delivering well-written and high-quality code 
• Presenting your results (we share our findings with team mostly during our catch-up meetings) 
• Requiring keeping yourself updated with state-of-the-art ML libraries and implementation of new paradigm to improve internal processes 

Must Haves 
• A Master or PhD in, Computer Science, Mathematics, Computer Vision/Machine Learning or similar related field 
• Proven ability to design and build computer vision networks using Pytorch 
• Proficient in Python and managing multi-repo libraries with large codebases 
• Excellent software engineer with knowledge of good software development practices 
• Knowledge of AI model training and validation processes, libraries and common optimization frameworks 
• Experience with CI/CD pipelines 

Nice to Haves
• Knowledge of AWS cloud and experience with their services (EKS, ECS, ...) and docker 
• Knowledge of C++ and CUDA, and ideally experience writing customer kernels / operators 
• Proficiency in distributed AI training techniques and parallel processing methods 
• Knowledge of recent Deep Learning and Computer Vision architectures 
• Data visualization experience would also be useful for this role 
• Excellent communicator - You are comfortable talking with programmers, marketers, surgeons, business leaders, and everyone in-between 

We Offer
We offer a competitive salary and benefits package to all our employees:
• Flexible working environment
• Annual Incentive Plan % depending on company results
• Pension scheme and group discount on healthcare insurance 
• Training possibilities via Cornerstone/Skills Lab
• Employee Assistance Program and Recognize! (our global recognition program)

Our Commitment
Our unwavering commitment to inclusion, diversity, and equity (ID&E) means zero barriers to opportunity within Medtronic and a culture where all employees belong, are respected, and feel valued for who they are and the life experiences they contribute. We know equity starts beyond our workplace, and we must play a role in addressing systemic inequities in our communities if we hope to have long-term sustainable impact. Anchored in our Mission, we continue to drive ID&E forward both to enhance the well-being of Medtronic employees and to accelerate innovation that brings our lifesaving technologies to more people in more places around the world. 

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

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

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.