Head of Machine Learning

Gloo
Bristol
2 months ago
Applications closed

Related Jobs

View all jobs

Head of Software Development

Head of Software Engineering (Java)

Head of Bioinformatics

Data Scientist

Senior IT Engineer

Digital Development Manager

We are seeking a Head of Machine Learning to lead an innovative team at the intersection of biotechnology and artificial intelligence. This role focuses on applying advanced AI and machine learning techniques to optimize and advance the manufacturing of human tissue for research and therapeutic applications.

The position requires a leader who can guide the deployment of machine learning models into production while collaborating across teams. This includes working with engineering teams on infrastructure and internal applications and biology teams on cell experiments, microscopy data collection, and differentiation protocol development.


About You

You should have:

  • Extensive experience leading Deep Learning teams.
  • Expertise in machine learning for computer vision.
  • Hands-on experience with modern ML tools and frameworks (e.g., PyTorch, Detectron) in production environments.
  • Experience developing software for data management and analysis, especially in collaboration with biology teams.


Key Responsibilities

  • Lead the AI/ML team, providing strategic and technical direction.
  • Develop training, testing, and deployment infrastructure for machine learning models.
  • Drive the selection and engineering of models for production, including choosing appropriate ML frameworks.
  • Collaborate with cross-functional teams to deliver impactful project outcomes.
  • Create internal applications and data products to support biological research.


Requirements

  • 3+ years of experience in a leadership role within a technology or ML-driven team.
  • Strong proficiency in Python, ML frameworks like PyTorch, cloud infrastructure, and CI systems.
  • Exceptional communication skills for clear, data-driven decision-making.


Preferred Qualifications

  • Interest or experience in biotechnology or biology.
  • Background working with large datasets or scientific research publications.
  • Experience developing AI-first software products, particularly in the biotech field.


What We Offer

  • The opportunity to work at the cutting edge of AI, stem cell biology, and cell therapy development.
  • An inclusive, collaborative, and intellectually stimulating work environment.


If you are passionate about leveraging machine learning to drive meaningful advancements in biotechnology, this is the perfect opportunity for you.

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.

Careers

10 Ways AI Pros Stay Inspired: Boost Creativity with Side Projects, Hackathons & More

In the rapidly evolving world of Artificial Intelligence (AI), creativity and innovation are critical. AI professionals—whether data scientists, machine learning engineers, or research scientists—must constantly rejuvenate their thinking to solve complex challenges. But how exactly do these experts stay energised and creative in their work? The answer often lies in a combination of strategic habits, side projects, hackathons, Kaggle competitions, reading the latest research, and consciously stepping out of comfort zones. This article will explore why these activities are so valuable, as well as provide actionable tips for anyone looking to spark new ideas and enrich their AI career. Below, we’ll delve into tried-and-tested strategies that AI pros employ to drive innovation, foster creativity, and maintain an inspired outlook in an industry that can be both exhilarating and daunting. Whether you’re just starting your AI journey or you’re an experienced professional aiming to sharpen your skills, these insights will help you break out of ruts, discover fresh perspectives, and bring your boldest ideas to life.

Careers

Top 10 AI Career Myths Debunked: Key Facts for Aspiring Professionals

Artificial Intelligence (AI) is one of the most dynamic and rapidly growing sectors in technology today. The lure of AI-related roles continues to draw a diverse range of job seekers—from seasoned software engineers to recent graduates in fields such as mathematics, physics, or data science. Yet, despite AI’s growing prominence and accessibility, there remains a dizzying array of myths surrounding careers in this field. From ideas about requiring near-superhuman technical prowess to assumptions that machines themselves will replace these jobs, the stories we hear sometimes do more harm than good. In reality, the AI job market offers far more opportunities than the alarmist headlines and misconceptions might suggest. Here at ArtificialIntelligenceJobs.co.uk, we witness firsthand the myriad roles, backgrounds, and success stories that drive the industry forward. In this blog post, we aim to separate fact from fiction—taking the most pervasive myths about AI careers and debunking them with clear, evidence-based insights. Whether you are an established professional considering a career pivot into data science, or a student uncertain about whether AI is the right path, this article will help you gain a realistic perspective on what AI careers entail. Let’s uncover the truth behind the most common myths and discover the actual opportunities and realities you can expect in this vibrant sector.

Jobs

Global vs. Local: Comparing the UK AI Job Market to International Landscapes

How to navigate salaries, opportunities, and work culture in AI across the UK, the US, Europe, and Asia Artificial Intelligence (AI) has evolved from a niche field of research to an integral component of modern industries—powering everything from chatbots and driverless cars to sophisticated data analytics in finance and healthcare. The job market for AI professionals is consequently booming, with thousands of new positions posted each month worldwide. In this blog post, we will explore how the UK’s AI job market compares to that of the United States, Europe, and Asia, delving into differences in job demand, salaries, and workplace culture. Additionally, we will provide insights for candidates considering remote or international opportunities. Whether you are a freshly qualified graduate in data science, an experienced machine learning engineer, or a professional from a parallel domain looking to transition into AI, understanding the global vs. local landscape can help you make an informed decision about your career trajectory. As the demand for artificial intelligence skills grows—and borders become more porous with hybrid and remote work—the possibilities for ambitious job-seekers are expanding exponentially. This article will offer a comprehensive look at the various regional markets, exploring how the UK fares in comparison to other major AI hubs. We’ll also suggest factors to consider when choosing where in the world to work, whether physically or remotely. By the end, you’ll have a clearer picture of the AI employment landscape, and you’ll be better prepared to carve out your own path.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.