Senior Machine Learning Engineer - Computer Vision

London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Machine Learning Performance Engineer

Senior/Staff Machine Learning Engineer

Senior Backend Engineer – Train in Machine Learning – Full Remote

Senior Machine Learning Engineer - Computer Vision
A brilliant opportunity for a Machine Learning Engineer with strong experience in Computer Vision to join an exciting tech-for-good start-up in London, which is making technological advances and solutions using machine learning techniques within healthcare. Joining a company founded by experts in their field, this is an amazing opportunity to truly make a difference by helping in the advancement of diagnosis & treatment of disease.
Location: 4 days a week remote - 1 day a week in London
Salary: £60,000 - £92,000 per annum + comprehensive benefits including private medical, dental, opticians, life assurance and enhanced pension
Requirements for Senior Machine Learning Engineer - Computer Vision

  • At least 2 years experience working in a Machine Learning position
  • Strong knowledge of Computer Vision - and even better, if this was related to medical imaging
  • Proficient in programming, ideally in Python
  • Excellent academic history - you are very likely educated to Ph.D. level with a 2.1 or first class degree and at least AAB at A Level (or international equivalent)
  • Good communication skills
  • Strong problem-solving ability
  • Any experience with regulatory medical standards for AI being used within Medical Devices would be beneficial
    Responsibilities for Senior Machine Learning Engineer - Computer Vision
  • Designing and refining machine learning models for medical imaging applications.
  • Enhancing model deployment by optimising training across multiple GPUs and distributed systems.
  • Creating efficient, high-performance inference pipelines.
  • Incorporating the latest research to develop innovative machine learning solutions.
  • Maximising computational efficiency to improve resource utilisation.
  • Establishing performance metrics to monitor and evaluate models over time.
    What this offers:
  • An opportunity to join a success story in the making
  • Working in tech-for-good
  • A super friendly, supportive culture with people on a mission to improve lives
    Applications:
    If you would like to enquire about this unique Machine Learning Engineer opportunity, we would love to hear from you.
    We're committed to creating an inclusive and accessible recruitment process. If you require reasonable adjustments for your application or during the review process, please highlight this by emailing (if this email address has been removed by the job-board, full details for contact are available on our website).
    ***********************************************************************************************
    RedTech Recruitment Ltd focuses on finding roles for Engineers and Scientists. Even if the above role isn’t of interest, please visit our website to see our other opportunities.
    We are an equal-opportunity employer and value diversity at RedTech. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
    Keywords– Machine Learning Engineer / Computer Vision / Medical Imaging / AI in Healthcare / Deep Learning / Artificial Intelligence (AI) / Data Science / AI Research / Python / PyTorch / Parallel Computing / GPU Acceleration / Multi-GPU Training / High-Performance Computing (HPC) / Scalable Inference Pipelines / Cloud Computing (AWS, GCP, Azure) / Docker / Containerization / Linux / Git / ML Development Tools/ MLFlow / Comet / Model Performance Tracking / Computational Resource Optimisation / AI as a / AIaMD / Agile Development / Software Engineering / Production-Grade Code / Testable & Maintainable Code / Research Implementation

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.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

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.