580 AI Evangelist jobs in the United Kingdom

Job title: Machine Learning Engineer

Locations: Manchester or Haywards Heath (hybrid working)

Role overview

Markerstudy Group have an exciting opportunity for a machine learning engineer to fill out the automation, pipelining, DevOps, and modelling aspects of Markerstudy’s market-leading technical modelling and pricing team. You will productionise novel insurance modelling processes as an automated machine learning pipeline within a cloud-based environment.

Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1b. Most of Markerstudy’s business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury’s, O2, Halifax, AA, Saga and Lloyds Bank to list a few.

As a Machine Learning Engineer, you will help build and maintain the pricing team’s MLOps and ML Lifecycle environment to support the creation of pipelines by automating the sophisticated machine learning models and processes that underpin our market-leading technical modelling and pricing function.

Key Responsibilities:

• Build an MLOps / DevOps environment to support machine learning automation
li>Build the pipelines that automate the regular model update and monitoring processes
• Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation, and communication processes.
• Work closely with the data science team to integrate modelling approaches and techniques

Key Skills and Experience:

• Previous experience as a DevOps / MLOps engineer
• Experience in Azure ML or databricks, or similar industry approved technology stack (i.e. AWS, Kubernetes and Docker, Google Cloud)
• Understanding of machine learning models and the modelling process, from data ingestion and cleaning to deployment and modelling – from the ground-up, not only through the use of packages and libraries
< i>Proficient at communicating results in a concise manner both verbally and written
• Previous industry experience in a STEM role or educated to the Master’s level in a STEM or DS / ML / AI or maths-based discipline.

Behaviours:

< i>Collaborative and team player
• Logical thinker with a professional and positive attitude
• Passion to innovate and improve processes
• Strong grasp of industry standards, and proficient in either Python, R, or both

Job title: Machine Learning Engineer

Locations: Manchester or Haywards Heath (hybrid working)

Role overview

Markerstudy Group have an exciting opportunity for a machine learning engineer to fill out the automation, pipelining, DevOps, and modelling aspects of Markerstudy’s market-leading technical modelling and pricing team. You will productionise novel insurance modelling processes as an automated machine learning pipeline within a cloud-based environment.

Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1b. Most of Markerstudy’s business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury’s, O2, Halifax, AA, Saga and Lloyds Bank to list a few.

As a Machine Learning Engineer, you will help build and maintain the pricing team’s MLOps and ML Lifecycle environment to support the creation of pipelines by automating the sophisticated machine learning models and processes that underpin our market-leading technical modelling and pricing function.

Key Responsibilities:

• Build an MLOps / DevOps environment to support machine learning automation
li>Build the pipelines that automate the regular model update and monitoring processes
• Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation, and communication processes.
• Work closely with the data science team to integrate modelling approaches and techniques

Key Skills and Experience:

• Previous experience as a DevOps / MLOps engineer
• Experience in Azure ML or databricks, or similar industry approved technology stack (i.e. AWS, Kubernetes and Docker, Google Cloud)
• Understanding of machine learning models and the modelling process, from data ingestion and cleaning to deployment and modelling – from the ground-up, not only through the use of packages and libraries
< i>Proficient at communicating results in a concise manner both verbally and written
• Previous industry experience in a STEM role or educated to the Master’s level in a STEM or DS / ML / AI or maths-based discipline.

Behaviours:

< i>Collaborative and team player
• Logical thinker with a professional and positive attitude
• Passion to innovate and improve processes
• Strong grasp of industry standards, and proficient in either Python, R, or both

Are you a Junior Machine Learning Engineer eager to turn messy, complex data into real-world intelligence?

We’re looking for a curious and motivated Junior ML Engineer to join a hybrid-working team building cutting-edge data intelligence tools for the financial sector. You’ll spend part of your time collaborating in person with engineers and data scientists, and part working remotely — giving you the best of both worlds.

You’ll be working on a platform that transforms unstructured private market data into actionable insights — learning how to design ML pipelines, fine-tune NLP models, and deploy solutions that really work in production.

In this role, you’ll help train, test, and optimise models that can read, understand, and structure complex documents at scale. From data preprocessing to model evaluation, you’ll gain hands-on experience across the machine learning lifecycle — while contributing to a product used by real-world clients.

What’s in it for you?

AI That Matters – Work on models that make sense of unstructured financial documents and turn them into structured insights.

Hands-On ML Experience – Learn the full ML workflow — from cleaning data to deploying models and monitoring them in production.

Mentorship & Growth – Work closely with experienced ML engineers who will guide your technical and career development.

Are you a Junior Machine Learning Engineer eager to turn messy, complex data into real-world intelligence?

We’re looking for a curious and motivated Junior ML Engineer to join a hybrid-working team building cutting-edge data intelligence tools for the financial sector. You’ll spend part of your time collaborating in person with engineers and data scientists, and part working remotely — giving you the best of both worlds.

You’ll be working on a platform that transforms unstructured private market data into actionable insights — learning how to design ML pipelines, fine-tune NLP models, and deploy solutions that really work in production.

In this role, you’ll help train, test, and optimise models that can read, understand, and structure complex documents at scale. From data preprocessing to model evaluation, you’ll gain hands-on experience across the machine learning lifecycle — while contributing to a product used by real-world clients.

What’s in it for you?

AI That Matters – Work on models that make sense of unstructured financial documents and turn them into structured insights.

Hands-On ML Experience – Learn the full ML workflow — from cleaning data to deploying models and monitoring them in production.

Mentorship & Growth – Work closely with experienced ML engineers who will guide your technical and career development.

Snap Inc ( is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company's three core products are Snapchat ( , a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio ( , an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles ( .
We're looking for Machine Learning Engineers to join the Generative ML Platform team at Snap Inc!
What you'll do:
+ Develop ML-tools and ML-products that serve millions of Snapchatters on a daily basis
+ Build cutting-edge augmented reality experiences with diffusion/flow matching models and GANs
+ Deliver GenAI experiences for the edge devices
+ Work on state of the art GenAI pipelines for image and video generation
+ Work closely with other Snap teams to introduce, prototype and launch new products
Knowledge, Skills & Abilities:
+ A proven passion for machine learning; you stay up-to-date with research and are excited about prototyping new ideas quickly
+ Knowledge of mathematics and deep learning foundations
+ Ability to effectively collaborate with internal teams and external partners
+ Ability to work independently
Minimum Qualifications:
+ Bachelor's Degree in a technical field such as computer science, mathematics, statistics or equivalent years of experience
+ Engineering experience in one or more of the following: neural rendering, generative models, segmentation, object detection, classification, tracking, or other related applications of deep learning
+ Experience with the major deep learning frameworks: PyTorch or TensorFlow
+ Strong programming skills in Python or C+Preferred Qualifications:
+ Experience developing real-time software for mobile applications
+ Knowledge of computer graphics foundations
+ Track record of successful projects in GenAI field
+ Examples of your work such as open source projects, blog posts, Kaggle contests, top conference or journal publications, etc.
If you have a disability or special need that requires accommodation, please don't be shy and provide us some information ( .
"Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a "default together" approach and expect our team members to work in an office 4+ days per week.
At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.
Our Benefits ( : Snap Inc. is its own community, so we've got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap's long-term success!
**A Decade of Snap ( **:** Learn about our origin story, values, mission, culture of innovation, and more.
**CitizenSnap ( **:** In our third annual CitizenSnap Report, we demonstrate progress towards our environmental, social, and governance (ESG) goals, and we lay out our plans looking forward.
**The DEI Innovation Summit ( **:** Watch highlights from the 2nd annual DEI Innovation Summit, which brings together thought leaders and DEI experts for a day of courageous conversations to enable bold action.
**Snap News ( **:** Stay up to date on the latest and greatest product and innovation news at Snap
Applicant and Candidate Privacy Policy (

About Us:
We are the leader in human-centric cybersecurity. Half a million customers, including 87 of the Fortune 100, rely on Proofpoint to protect their organizations. We're driven by a mission to stay ahead of bad actors and safeguard the digital world. Join us in our pursuit to defend data and protect people.
How We Work:
At Proofpoint, you'll be part of a global team that breaks barriers to redefine cybersecurity, guided by our BRAVE core values: Bold in how we dream and innovate, Responsive to feedback, challenges, and opportunities, Accountable for results and best-in-class outcomes, Visionary in future-focused problem-solving, Exceptional in execution and impact.
Corporate Overview
Proofpoint is a leading cybersecurity company protecting organizations' greatest assets and biggest risks: vulnerabilities in people. With an integrated suite of cloud-based solutions, Proofpoint helps companies around the world stop targeted threats, safeguard their data, and make their users more resilient against cyber-attacks. Leading organizations of all sizes, including more than half of the Fortune 1000, rely on Proofpoint for people-centric security and compliance solutions mitigating their most critical risks across email, the cloud, social media, and the web.
We are singularly devoted to helping our customers protect their greatest assets and biggest security risk: their people. That's why we're a leader in next-generation cybersecurity.
Protection Starts with People. Proofpoint.
**The Role**
Proofpoint is looking for a Machine Learning Scientist to join the Algo team within the Tessian Business Unit. In this role, your key responsibility will be to analyse data, build ML models and improve algorithms at the core of our email threat detection engine that protects some of the largest businesses in the world. You will collaborate with Product and Engineering teams to identify and solve the most impactful problems applying state-of-the-art machine learning tools and techniques. You'll be surrounded by incredibly smart, talented and friendly colleagues. Engineers at Tessian love to learn from each other and pull together as a team to succeed.
*This is a Hybrid role; Cork or Belfast.
**Your day-to-day**
-Wrangle and draw meaningful insights from massive amounts of unstructured textual data using the latest tools and technologies like Spark, Iceberg, Athena, AWS SageMaker
-Apply unsupervised learning algorithms across billions of email interactions to identify emerging threat patterns
-Work with state-of-the-art machine learning models and techniques like encoder-decoder transformers, LLMs, anomaly detection as well as classical ML models to solve a multifaceted problem
-Engineer new features, train and deploy models to production using AWS SageMaker as the MLOps platform
-Adopt a data-driven approach to identify gaps in our detection algorithms and propose improvements to our models and algorithms
-Promote and drive ML best practices and cultivate an environment of experimentation and learning
-Stay up to date with the latest advancements in machine learning, AI technologies, and incorporate them into our solutions where applicable
**What you bring to the team**
Essential
- Proficiency in Python with the ability to write clean, well-structured, and maintainable code for data analysis, modeling and experimentation
- Experience contributing to multiple highly impactful machine learning projects with proven results
-Hands-on experience in the NLP domain involving training, fine-tuning and productionising transformer-based models for text classification / text-embeddings (experience with LLMs, generative AI is a plus)
-Experience monitoring and maintaining performance of models over time in production considering model/data drifts In-depth experience with one or more deep neural network frameworks (e.g. PyTorch, Tensorflow, JAX)
-A creative mindset, propensity to care deeply about the impact their team has and to encourage novel ways of critical thinking in their team
Good to have
-Conceptual understanding of Graph Neural Networks and experience applying GNNs to solve real world problem statements will be a plus
-Experience working on large imbalanced datasets, evaluating and selecting models that work well in production on imbalanced real-world data
Why Proofpoint
Protecting people is at the heart of our award-winning lineup of cybersecurity solutions, and the people who work here are the key to our success. We're a customer-focused and a driven-to-win organization with leading-edge products. We are an inclusive, diverse, multinational company that believes in culture fit, but more importantly 'culture-add', and we strongly encourage people from all walks of life to apply.
We believe in hiring the best and the brightest to help cultivate our culture of collaboration and appreciation. Apply today and explore your future at Proofpoint! #LifeAtProofpoint
#LI-Hybrid
Why Proofpoint? At Proofpoint, we believe that an exceptional career experience includes a comprehensive compensation and benefits package. Here are just a few reasons you'll love working with us:
- Competitive compensation
- Comprehensive benefits
- Learning & Development: We are committed to the growth and development of our team members, offering a range of programs including leadership and professional development workshops, stretch project assignments, and mentoring opportunities to help employees reach their full potential.
- Flexible work environment: (Remote options, hybrid schedules, flexible hours, etc.).
- Annual wellness and community outreach days
- Always on recognition for your contributions
- Global collaboration and networking opportunities
Our Culture:
Our culture is rooted in values that inspire belonging, empower purpose and drive success-every day, for everyone. We encourage applications from individuals of all backgrounds, experiences, and perspectives. If you need accommodation during the application or interview process, please reach out to . How to Apply Interested? Submit your application here . We can't wait to hear from you!
Proofpoint has been honored with six Best Places to Work Awards in 2024 by workplace culture leader Comparably, including Best Company Career Growth, Best Company Outlook, Best Global Culture, Best Engineering Teams, Best Sales Teams, and Best HR Teams.
We are the leader in human-centric cybersecurity. Half a million customers, including 87 of the Fortune 100, rely on Proofpoint to protect their organizations. We're driven by a mission to stay ahead of bad actors and safeguard the digital world. Join us in our pursuit to defend data and protect people.
Our BRAVE Values:
At Proofpoint, we are BRAVE in everything we do, and our values aren't just words-they shape how we work, collaborate, and grow.
We seek people who are bold enough to challenge the status quo, responsive in the face of ever-evolving threats, and accountable for delivering real impact.
We value those with a visionary mindset who anticipate what's next and push cybersecurity forward, and we celebrate exceptional execution that ensures we continue to defend data and protect people.
Proofpoint is an equal opportunity employer, we hire without consideration to race, religion, creed, color, national origin, age, gender, sexual orientation, marital status, veteran status or disability.
Find your network, your allies, and your biggest fans. We know that work is simply better when you're surrounded by people who inspire you-who share ideas, cheer you on, and genuinely want to see you succeed. That's why we offer social circles, sponsored networks, and connection points across teams and time zones-to help you find your people, build your community, and thrive together.
This isn't just a job-it's a mission to protect people and defend data in a world that never slows down. We're building the future of human-centric cybersecurity, and that future belongs to all of us. We take ownership, move fast, and hold ourselves accountable-because that's what it takes to stay ahead. And we do it together, winning as one.
Be empowered to reach your full potential through meaningful challenges and personalized support-designed around you and your goals. Whether you're growing as a leader or leveling up from great to exceptional as an individual contributor, we're here to help you get there.
Proofpoint is an equal opportunity employer, we hire without consideration to race, religion, creed, color, national origin, age, gender, sexual orientation, marital status, veteran status or disability.

Machine Learning Engineer and Data Engineer Location: London Type: Full-time | Permanent | Office based Salary: up to £100,000 (ML Engineer) and up to £80,000 (Data Engineer) About Us We’re an early-stage startup on a mission to. As we scale, we’re looking for a Machine Learning Engineer and Data Engineer who are excited to build real-world products from the ground up, shape the future of our technology, and make a measurable impact. The Role You’ll play a key role in designing, building, and deploying ML models that power our core product. This isn’t just about research — it’s about turning ideas into features customers love. You’ll work closely with our founding team, own projects end-to-end, and help set the standard for engineering practices as we grow. What You’ll Do Design, train, and deploy machine learning models to solve real-world problems. Collaborate with product and engineering teams to integrate ML into customer-facing features. Build scalable data pipelines and infrastructure to support model training and inference. Experiment with new algorithms and techniques, bringing the latest research into production. Monitor and optimise models for performance, accuracy, and efficiency. Contribute to technical decisions that balance immediate needs with long-term scalability. Help shape our technical culture, processes, and roadmap as an early team member. What We’re Looking For 2 years’ experience as a Machine Learning Engineer, Data Scientist, or similar role. Strong background in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with building and deploying ML models into production. Knowledge of APIs, data pipelines, and cloud infrastructure (AWS, GCP, or Azure). Strong problem-solving skills and ability to work independently in a fast-paced environment. Curiosity, openness, and a willingness to experiment and learn. Excellent communication skills for explaining complex concepts to technical and non-technical audiences. Nice to Have Experience working in a startup or high-growth tech environment. Familiarity with AI-assisted coding tools (e.g. GitHub Copilot, Cursor).

Who We Are At Ultralytics , we relentlessly drive innovation in AI, building the world's leading open-source models . We're looking for passionate individuals obsessed with AI, eager to make a global impact, and ready to excel in a dynamic, high-energy environment. Join our team and help shape the future of Vision AI . Location and Legalities This full-time Machine Learning Engineer position is based onsite in our brand-new Ultralytics office in London, UK. Applicants must have legal authorization to work in the UK, as Ultralytics does not provide visa sponsorship. What You'll Do As a Machine Learning Engineer at Ultralytics, you will be at the forefront of developing and refining our world-class Ultralytics YOLO models. You will work on the entire lifecycle of our models, from research and development to high-performance deployment. Key responsibilities include: Developing, training, and validating state-of-the-art models for a variety of computer vision tasks , including detection, segmentation, and classification. Writing highly efficient, scalable, and production-ready code in Python using the PyTorch framework. Optimizing models for high-performance inference on diverse hardware using tools like NVIDIA TensorRT , OpenVINO , and ONNX . Managing and processing large-scale datasets and implementing advanced data augmentation strategies. Designing and maintaining robust CI/CD pipelines with GitHub Actions for automated model training, testing, and benchmarking. Collaborating with our research and engineering teams to implement cutting-edge techniques and contribute to our open-source repositories . Engaging with our global community by creating documentation, tutorials, and supporting users to solve real-world problems with our technology. Your expertise will be critical in advancing the capabilities of our models and supporting Ultralytics' mission to make AI easy and accessible for everyone. ️ Skills and Experience 5 years of professional experience in Machine Learning Engineering or a similar role. Deep expertise in Python and deep learning frameworks, with a strong preference for PyTorch . Proven experience with computer vision and a strong understanding of model architectures like transformers and CNNs. Hands-on experience with model optimization (i.e. quantization, pruning) and model deployment frameworks such as TensorRT , ONNX Runtime , and OpenVINO . Proficiency with CUDA programming and optimizing code for GPU acceleration. Strong background in MLOps practices, including CI/CD using GitHub Actions and containerization with Docker . Excellent problem-solving skills and the ability to thrive in a fast-paced, high-intensity environment. Experience contributing to major open-source projects is a significant advantage. Cultural Fit - Intensity Required Ultralytics is a high-performance environment for world-class talent obsessed with achieving extraordinary results. We operate at a relentless pace, demanding exceptional dedication and an unwavering commitment to excellence, guided by our mission, vision, and values . Our team thrives on audacious goals and absolute ownership. This is not a conventional workplace. If your priority is predictable comfort or a standard work-life balance over the relentless pursuit of progress, Ultralytics is not for you. We seek driven individuals prepared for the profound personal investment required to make a defining contribution to the future of AI. Compensation and Benefits Competitive Salary: Highly competitive based on experience. Startup Equity: Participate directly in our company's growth and success. Hybrid Flexibility: 3 days per week in our brand-new office - 2 days remote. Generous Time Off: 24 days vacation, your birthday off, plus local holidays. Flexible Hours: Tailor your working hours to suit your productivity. Tech: Engage with cutting-edge AI projects . Gear: Brand-new Apple MacBook and Apple Display provided. Team: Become part of a supportive and passionate team environment . If you are driven to redefine the capabilities of machine learning and eager to make a significant impact, Ultralytics offers an exceptional career opportunity.

Machine Learning Engineer and Data Engineer Location: London Type: Full-time | Permanent | Office based Salary: up to £100,000 (ML Engineer) and up to £80,000 (Data Engineer) About Us We’re an early-stage startup on a mission to. As we scale, we’re looking for a Machine Learning Engineer and Data Engineer who are excited to build real-world products from the ground up, shape the future of our technology, and make a measurable impact. The Role You’ll play a key role in designing, building, and deploying ML models that power our core product. This isn’t just about research — it’s about turning ideas into features customers love. You’ll work closely with our founding team, own projects end-to-end, and help set the standard for engineering practices as we grow. What You’ll Do Design, train, and deploy machine learning models to solve real-world problems. Collaborate with product and engineering teams to integrate ML into customer-facing features. Build scalable data pipelines and infrastructure to support model training and inference. Experiment with new algorithms and techniques, bringing the latest research into production. Monitor and optimise models for performance, accuracy, and efficiency. Contribute to technical decisions that balance immediate needs with long-term scalability. Help shape our technical culture, processes, and roadmap as an early team member. What We’re Looking For 2 years’ experience as a Machine Learning Engineer, Data Scientist, or similar role. Strong background in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with building and deploying ML models into production. Knowledge of APIs, data pipelines, and cloud infrastructure (AWS, GCP, or Azure). Strong problem-solving skills and ability to work independently in a fast-paced environment. Curiosity, openness, and a willingness to experiment and learn. Excellent communication skills for explaining complex concepts to technical and non-technical audiences. Nice to Have Experience working in a startup or high-growth tech environment. Familiarity with AI-assisted coding tools (e.g. GitHub Copilot, Cursor).