What Jobs are available for Machine Learning Engineers in London?

Job Title: Machine Learning Engineer

Location: London, UK (Hybrid – 2–3 days onsite per week)

Contract Type: Contract

Duration: 6–12 months (possibility of extension)

Start Date: ASAP

Overview

We are seeking an experienced Machine Learning Engineer to join our data science and AI engineering team on a contract basis in London. The ideal candidate will be responsible for designing, developing, and deploying machine learning models and scalable data pipelines that support advanced analytics and intelligent automation initiatives.

This role offers a hybrid work arrangement , combining flexibility with collaboration, and is ideal for a contractor who thrives in fast-paced, data-driven environments.

Key Responsibilities

• Design, build, and deploy machine learning models and AI-driven solutions to address business challenges.
• Collaborate with data scientists to transition prototypes into production-ready systems .
• Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment.
• Optimise model performance, scalability, and reliability using MLOps best practices.
• Work with large-scale structured and unstructured datasets for model training and validation.
• Implement model monitoring, versioning, and retraining processes to ensure continuous improvement.
• Collaborate cross-functionally with engineering, data, and product teams to integrate ML solutions into production environments.
• Stay current with emerging trends in AI/ML technologies and contribute to innovation within the organisation.

Required Skills & Experience

• Proven experience (3–5+ years) as a Machine Learning Engineer , Data Scientist , or similar role.
• Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy).
• Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures .
• Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI).
• Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms.
• Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration.
• Knowledge of containerization and orchestration tools (Docker, Kubernetes).
• Experience integrating ML models into production environments via APIs or microservices.
• Excellent problem-solving, analytical, and communication skills.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science , Data Science , Mathematics , or a related field.
• Familiarity with CI/CD pipelines for ML model deployment.
• Exposure to natural language processing (NLP) , computer vision , or reinforcement learning projects.
• Experience working in Agile/Scrum environments.

Contract Details

• Location: Hybrid – London (onsite 2–3 days per week)
• Type: Day-rate contract (Outside/Inside IR35 subject to assessment)
• Duration: 6–12 months (extension likely)
• Start Date: Immediate or within 2–4 weeks

Why Join

• Work with a talented, cross-functional AI and data engineering team.
• Contribute to cutting-edge ML solutions in a collaborative, innovation-driven environment.
• Hybrid flexibility with a strong London presence.

Working Pattern : Hybrid (1-2 days per week in office)

Location : London

As a company for whom AI is the product, it should be no surprise that our Data Science team is at the heart of everything we do at Sprout - building innovative products, researching new techniques for using Artificial Intelligence in claims automation, and pushing the boundaries of what our product can achieve. 

As a globally dispersed team, our Data Science team brings together a diverse range of expertise and backgrounds; what unites us is a desire to learn, a mastery of our discipline, strong mathematical and statistical skills, and software engineering prowess. We typically specialise in fields such as Computer Vision, LLMs and Deep Learning. 

Our Machine Learning Engineers are responsible for all aspects of the AI lifecycle, from understanding business problems, preparing training data, assisting the data scientists in designing and building models, and deploying them into production. We work in cross-functional squads, so you will work collaboratively with Data Scientists, Software Engineers, Product and Engagement Managers on your designated project.

You will not only work on the development and productionisation of sophisticated ML products, but also shape the future of our AI capabilities. You will have the opportunity to mentor junior team members, influence strategic decisions, and directly impact our customers’ experiences.

If you are passionate about transforming industries with AI and want to work with an innovative, ambitious team, we would love to hear from you. Apply now and help shape the future of claims automation.

• Develop features for our state-of-the-art claims automation platform
• Build and deploy machine learning algorithms and models to production within product teams
• Provide technical guidance and input on the design and implementation of machine learning algorithms
• Support with customer PoVs and onboarding
• Understand business problems and product requirements and help translate these into technical solutions
• Execute and deliver full AI/ML solutions from sourcing training data, design and implementing state-of-the-art machine learning models, testing, benchmark and product-driven research for model performance improvement, to shipping stable, tested, performant code in an agile environment.
• Work closely with Product Managers to help shape the product roadmap from a Data Science perspective
• Contribute to Data Science strategy and the technical roadmap in conjunction with our Head of AI
• Proactively seek to improve the way that Data Science operates at Sprout.ai
• Support the education of the business and customers on how our Data Science teams work
• Stay updated on the latest trends and advancements in Artificial Intelligence.

• Technical proficiency
• You write production-grade, scalable Python code, ensuring that your models are robust, maintainable, and optimised for performance.
• Comfortable with PyTorch
• Knowledge of Transformer-based models
• Knowledge of Large Language Models (LLMs)
• Proven experience of having delivered successful machine learning projects into production 
• Strong understanding of software development fundamentals, in particular deploying models to production and how to set up pipelines.
• Demonstrate expertise in deep learning for computer vision, natural language processing, reinforcement learning etc
• Displays in depth knowledge in machine learning best practices, scalable training and deployment, model introspection and evaluation
• Understanding of the fundamentals in Mathematics, Statistics and Data Analysis
• Experience working in an Agile environment and knowledge of how Agile methodologies can be applied to Data Science teams in terms of process, practice, team culture and the delivery of work
• Ability to convert customer requirements or business challenges into well-defined machine learning solutions
• We are using many technologies day to day such as various AWS services, GCP, Kubernetes, Ray Serve, Kubeflow, and ReTool. Any experience in these areas would be a bonus

• Design, develop, train and optimise scalable ML models for far-field voice detection, verification, and enhancement across Sky devices and cloud platforms.

• Contribute to innovation discussions and research in applied speech, audio signal processing, ASR, NLP and machine learning.

• Build and construct cloud-based ML pipelines and APIs that process real-time audio streams at scale.

• Work closely with data scientists, audio engineers, product managers, and external partners to deliver robust and accurate voice experiences.

• Develop and document technical specifications, ensuring solutions meet latency, performance, and reliability requirements.

• Monitor system metrics and production model performance to proactively identify opportunities for improvement.

• Ensure best practices for ML operations (MLOps), including continuous integration, model deployment, and automated testing.

• Provide technical guidance, code reviews, and mentorship to junior members of the team.

• Demonstrated ability across the full ML lifecycle: model development, deployment, monitoring, and maintenance, with solid theoretical knowledge from classic approaches to state-of-the-art techniques.
• Technical Skills and Coding Practices
  Proven ability to refactor and write performant, secure, and clean code; strong experience with Python and ML libraries/frameworks, plus a desire to learn additional languages.
• Cloud and Infrastructure Experience
  Hands-on experience with cloud services commonly used in serverless applications, following best practices (e.g., AWS Lambda), and working with CI/CD in agile teams.
• Large-Scale and Customer-Facing Solutions
  Strong experience building in-house models and solutions for customer-facing products, including large-scale ML systems serving tens of millions of users.
• Product Development and Delivery
  End-to-end product development skills with a passion for technology, fast-paced delivery, and a restless attitude to continuously improve speed and quality.
• Leadership and Collaboration
  Good communicator, team player, and tech leader who can also contribute individually; strong positive attitude toward success and failure.
• Analytical and Innovative Mindset
  Strong analytical skills with measurable impact, familiarity with Generative AI and its production applications, and a drive to innovate.
• Academic and Research Excellence (Big Plus)
  PhD in related subjects, extensive ML research background, academic publications in ML conferences/journals, and experience developing ML products for Voice, ASR, and NLP at scale.

• Sky Q, for the TV you love all in one place

• The magic of Sky Glass at an exclusive rate

• A generous pension package

• Private healthcare

• Discounted mobile and broadband

• A wide range of Sky VIP rewards and experiences

• Design, develop, train and optimise scalable ML models for far-field voice detection, verification, and enhancement across Sky devices and cloud platforms.

• Contribute to innovation discussions and research in applied speech, audio signal processing, ASR, NLP and machine learning.

• Build and construct cloud-based ML pipelines and APIs that process real-time audio streams at scale.

• Work closely with data scientists, audio engineers, product managers, and external partners to deliver robust and accurate voice experiences.

• Develop and document technical specifications, ensuring solutions meet latency, performance, and reliability requirements.

• Monitor system metrics and production model performance to proactively identify opportunities for improvement.

• Ensure best practices for ML operations (MLOps), including continuous integration, model deployment, and automated testing.

• Provide technical guidance, code reviews, and mentorship to junior members of the team.

• Demonstrated ability across the full ML lifecycle: model development, deployment, monitoring, and maintenance, with solid theoretical knowledge from classic approaches to state-of-the-art techniques.
• Technical Skills and Coding Practices
  Proven ability to refactor and write performant, secure, and clean code; strong experience with Python and ML libraries/frameworks, plus a desire to learn additional languages.
• Cloud and Infrastructure Experience
  Hands-on experience with cloud services commonly used in serverless applications, following best practices (e.g., AWS Lambda), and working with CI/CD in agile teams.
• Large-Scale and Customer-Facing Solutions
  Strong experience building in-house models and solutions for customer-facing products, including large-scale ML systems serving tens of millions of users.
• Product Development and Delivery
  End-to-end product development skills with a passion for technology, fast-paced delivery, and a restless attitude to continuously improve speed and quality.
• Leadership and Collaboration
  Good communicator, team player, and tech leader who can also contribute individually; strong positive attitude toward success and failure.
• Analytical and Innovative Mindset
  Strong analytical skills with measurable impact, familiarity with Generative AI and its production applications, and a drive to innovate.
• Academic and Research Excellence (Big Plus)
  PhD in related subjects, extensive ML research background, academic publications in ML conferences/journals, and experience developing ML products for Voice, ASR, and NLP at scale.

• Sky Q, for the TV you love all in one place

• The magic of Sky Glass at an exclusive rate

• A generous pension package

• Private healthcare

• Discounted mobile and broadband

• A wide range of Sky VIP rewards and experiences

• Design, develop, train and optimise scalable ML models for far-field voice detection, verification, and enhancement across Sky devices and cloud platforms.

• Contribute to innovation discussions and research in applied speech, audio signal processing, ASR, NLP and machine learning.

• Build and construct cloud-based ML pipelines and APIs that process real-time audio streams at scale.

• Work closely with data scientists, audio engineers, product managers, and external partners to deliver robust and accurate voice experiences.

• Develop and document technical specifications, ensuring solutions meet latency, performance, and reliability requirements.

• Monitor system metrics and production model performance to proactively identify opportunities for improvement.

• Ensure best practices for ML operations (MLOps), including continuous integration, model deployment, and automated testing.

• Provide technical guidance, code reviews, and mentorship to junior members of the team.

• Demonstrated ability across the full ML lifecycle: model development, deployment, monitoring, and maintenance, with solid theoretical knowledge from classic approaches to state-of-the-art techniques.
• Technical Skills and Coding Practices
  Proven ability to refactor and write performant, secure, and clean code; strong experience with Python and ML libraries/frameworks, plus a desire to learn additional languages.
• Cloud and Infrastructure Experience
  Hands-on experience with cloud services commonly used in serverless applications, following best practices (e.g., AWS Lambda), and working with CI/CD in agile teams.
• Large-Scale and Customer-Facing Solutions
  Strong experience building in-house models and solutions for customer-facing products, including large-scale ML systems serving tens of millions of users.
• Product Development and Delivery
  End-to-end product development skills with a passion for technology, fast-paced delivery, and a restless attitude to continuously improve speed and quality.
• Leadership and Collaboration
  Good communicator, team player, and tech leader who can also contribute individually; strong positive attitude toward success and failure.
• Analytical and Innovative Mindset
  Strong analytical skills with measurable impact, familiarity with Generative AI and its production applications, and a drive to innovate.
• Academic and Research Excellence (Big Plus)
  PhD in related subjects, extensive ML research background, academic publications in ML conferences/journals, and experience developing ML products for Voice, ASR, and NLP at scale.

• Sky Q, for the TV you love all in one place

• The magic of Sky Glass at an exclusive rate

• A generous pension package

• Private healthcare

• Discounted mobile and broadband

• A wide range of Sky VIP rewards and experiences

• Design, develop, train and optimise scalable ML models for far-field voice detection, verification, and enhancement across Sky devices and cloud platforms.

• Contribute to innovation discussions and research in applied speech, audio signal processing, ASR, NLP and machine learning.

• Build and construct cloud-based ML pipelines and APIs that process real-time audio streams at scale.

• Work closely with data scientists, audio engineers, product managers, and external partners to deliver robust and accurate voice experiences.

• Develop and document technical specifications, ensuring solutions meet latency, performance, and reliability requirements.

• Monitor system metrics and production model performance to proactively identify opportunities for improvement.

• Ensure best practices for ML operations (MLOps), including continuous integration, model deployment, and automated testing.

• Provide technical guidance, code reviews, and mentorship to junior members of the team.

• Demonstrated ability across the full ML lifecycle: model development, deployment, monitoring, and maintenance, with solid theoretical knowledge from classic approaches to state-of-the-art techniques.
• Technical Skills and Coding Practices
  Proven ability to refactor and write performant, secure, and clean code; strong experience with Python and ML libraries/frameworks, plus a desire to learn additional languages.
• Cloud and Infrastructure Experience
  Hands-on experience with cloud services commonly used in serverless applications, following best practices (e.g., AWS Lambda), and working with CI/CD in agile teams.
• Large-Scale and Customer-Facing Solutions
  Strong experience building in-house models and solutions for customer-facing products, including large-scale ML systems serving tens of millions of users.
• Product Development and Delivery
  End-to-end product development skills with a passion for technology, fast-paced delivery, and a restless attitude to continuously improve speed and quality.
• Leadership and Collaboration
  Good communicator, team player, and tech leader who can also contribute individually; strong positive attitude toward success and failure.
• Analytical and Innovative Mindset
  Strong analytical skills with measurable impact, familiarity with Generative AI and its production applications, and a drive to innovate.
• Academic and Research Excellence (Big Plus)
  PhD in related subjects, extensive ML research background, academic publications in ML conferences/journals, and experience developing ML products for Voice, ASR, and NLP at scale.

• Sky Q, for the TV you love all in one place

• The magic of Sky Glass at an exclusive rate

• A generous pension package

• Private healthcare

• Discounted mobile and broadband

• A wide range of Sky VIP rewards and experiences

We are a rapidly growing startup developing solutions that blend human expertise and AI agents to handle manual customer and marketplace operations tasks. Our unique approach combines the strengths of human expertise (high accuracy and nuanced decision-making) with the advantages of AI automation (speed and cost efficiency). This cutting-edge technology helps businesses solve real-world challenges in trust & safety and beyond without complex technical integration. We believe in an online world free from harm, where we can trust AI to make safe and fair decisions.

We have raised about $25M in VC funding from top tier funds including Creandum and Plural, and operate at significant scale - analysing millions of daily images and videos. But we are just at the beginning of our journey - and we are very excited about our plans for growth over the coming year and beyond

We are now looking for a Machine Learning Engineer to build and deliver innovative AI products to our customers. Your software expertise and machine learning knowledge will help transform our customers' manual processes into AI automated solutions.

Your mission will be to ensure our customers receive the most effective AI solutions for their specific needs. You will apply your technical and analytical skills to understand customer challenges and collaborate with them to leverage our AI in the automation of their work. Initially, you will provide hands-on support for our machine learning models as they come to market but then will gradually develop self-service tools that empower customers to achieve value independently.

As part of this role, you will:

• Collaborate with customers to thoroughly understand their workflows, then design and build AI agents that automate their processes.
• Contribute to the development of our AI agent development platform that scales with our product strategy.
• Ensure our AI services maintain high standards of reliability, observability, availability, and performance.
• Participate in our machine learning community to influence how we implement machine learning and computer vision technologies, shaping Unitary's future.
• Take ownership of customer outcomes with the autonomy to make decisions that surprise and delight our customers.
• Contribute full-stack development including software engineering, DevOps, and MLOps, along with light task and project management to ensure your AI solutions deliver maximum value.

We are looking for someone who is as excited about Unitary's mission as we are, who wants to have a large impact at an early-stage startup, and be a key part of defining Unitary's future as one of our early employees. We need versatile people who are happy to get stuck into whatever needs doing, and are ready to learn and grow with the company.

For this particular role, we need a proactive software engineering expert who is familiar with using AI tooling and prompt engineering, and who is comfortable engaging with customers and exploring and presenting new ideas. Strong communication skills are essential, as you'll lead technical deliveries and bring others along on the journey. You embrace a product mindset in everything you do and should demonstrate a genuine curiosity for solving current and future customer challenges.

We would love to hear from you if you:

• Have strong Python and engineering skills, with experience using and applying AI to solve customer problems
• Can (or want to learn to) develop agentic AI systems that can automate human processes
• Have an understanding of (or want to learn) how software is deployed through Kubernetes, and with the capability to deploy some infrastructure elements independently
• Can demonstrate problem solving and project management skills in order to analyse workflows and design automated solutions
• Thrive in a collaborative environment where group output and team achievements weigh heavier than individual input
• Can travel to our company-wide offsites three times per year

It would be even better, but not essential, if you have:

• Experience working in a fully remote, international team
• Previous startup experience
• A background in building and operating agentic AI systems
• Experience with MLOps practices and tools, and monitoring machine learning systems in production
• Knowledge of CI/CD practices and tools such as GitLab CI, Argo CD
• Proficiency with SQL and NoSQL databases
• Worked with Kubernetes and infrastructure as code (IaC) tools such as Terraform
• Experience with Large Language Models (LLMs) and a keen interest in staying current with the latest AI technology advancements

This role will report to the VP of Engineering and can be placed anywhere within 3 hours of the UK time zone.

Unitary is a remote-first team of c. 20 people spread across Europe and North America who are fiercely passionate about making the internet a safer place, and deeply motivated to become a force for good. We have an ambition to create a company filled with happy, kind and collaborative people who achieve extraordinary things together. Our culture is built around the power of trust, transparency and self-leadership.

Working at Unitary

We are committed to creating a positive and inclusive culture built on genuine interest for each other's well-being. We offer progressive and market-leading benefits, including:

• Flexible hours and location
• Competitive salary and equity package
• Occupational pension
• Generous paid parental leave
• Generous paid sick leave
• Annual budget for your professional development and growth
• Annual budget for your individual health and wellness
• Three team offsites to London or other exciting destinations in Europe