Explore exciting opportunities in the field of machine learning engineering. This role involves developing and implementing 967 Machine Learning Engineer jobs in the United Kingdom
Machine Learning Engineer
Job Viewed
Job Description
- Support end-to-end deployment of ML models (batch and real-time) from code validation through to production rollout under guidance from senior team members.
- Work with Data Science teams to facilitate smooth model handover and ensure deployment readiness aligned with implementation standards.
- Build and maintain CI/CD pipelines for model deployment, scoring, and operational monitoring.
- Debug and fix pipeline issues including data ingestion problems, model scoring failures, and deployment errors.
- Write comprehensive tests for ML pipelines (unit, integration, validation) and implement data quality checks and operational monitoring.
- Ensure deployed models meet audit, reconciliation, and governance requirements.
- Monitor production models for operational health, troubleshoot failures, and track data/variable drift over time.
- Work with Platform Engineers within the team to create reusable MLOps templates and support Data Scientists in using them effectively.
- Support model migrations across data sources, tools, systems, and platforms.
- Participate in code reviews, knowledge sharing, and pod activities (standups, grooming, delivery check-ins).
- Learn from senior team members and contribute to continuous improvement of model delivery practices.
- Solid Python engineering background with some experience in ML model deployment
- Familiarity with AWS services and cloud-based ML deployment (SageMaker experience preferred but not required)
- Basic understanding of data warehousing concepts and SQL (Snowflake experience a plus)
- Experience with or willingness to learn CI/CD tooling (e.g. GitHub Actions), containerization (Docker), and workflow orchestration tools (Airflow/AstroCloud)
- Strong debugging and troubleshooting skills for data pipelines and ML systems
- Experience writing tests (unit, integration) and implementing monitoring/alerting for production systems
- Strong data skills, including the ability to explore and validate datasets to ensure model inputs and outputs are correct
- Basic understanding of ML lifecycle concepts and willingness to learn about model registry, versioning, and deployment practices
- Experience collaborating with Data Science teams or similar cross-functional collaboration
- Understanding of software testing and validation practices, with willingness to learn model-specific governance requirements
- Ability to participate in code reviews and learn from feedback
- Good communication skills with both technical and business stakeholders
- Eagerness to learn and grow in ML engineering and deployment practices
- (Nice to have) Any exposure to MLflow, model monitoring, or MLOps tools
- (Nice to have) Experience with data pipeline tools or frameworks
- You're a motivated engineer who enjoys collaborative problem-solving and wants to grow your expertise in ML engineering.
- You care about code quality and are eager to learn about model deployment best practices, auditability, and production systems.
- You communicate well, ask thoughtful questions, and are excited to bridge the gap between Data Science experimentation and production-grade systems.
- You're interested in learning about deployment standards and the audit and reconciliation expectations that come with production ML.
- You're enthusiastic about contributing to automated and self-serve model deployment systems.
- You take initiative, are reliable in your commitments, and value learning from experienced team members.
- You appreciate structure and are committed to developing high standards in both technical delivery and communication.
What you will be doing - Support end-to-end deployment of ML models (batch and real-time) from code validation through to production rollout under guidance from senior team members.
- Work with Data Science teams to facilitate smooth model handover and ensure deployment readiness aligned with implementation standards.
- Build and maintain CI/CD pipelines for model deployment, scoring, and operational monitoring.
- Debug and fix pipeline issues including data ingestion problems, model scoring failures, and deployment errors.
- Write comprehensive tests for ML pipelines (unit, integration, validation) and implement data quality checks and operational monitoring.
- Ensure deployed models meet audit, reconciliation, and governance requirements.
- Monitor production models for operational health, troubleshoot failures, and track data/variable drift over time.
- Work with Platform Engineers within the team to create reusable MLOps templates and support Data Scientists in using them effectively.
- Support model migrations across data sources, tools, systems, and platforms.
- Participate in code reviews, knowledge sharing, and pod activities (standups, grooming, delivery check-ins).
- Learn from senior team members and contribute to continuous improvement of model delivery practices.
- Required Skills & Experience
- Solid Python engineering background with some experience in ML model deployment
- Familiarity with AWS services and cloud-based ML deployment (SageMaker experience preferred but not required)
- Basic understanding of data warehousing concepts and SQL (Snowflake experience a plus)
- Experience with or willingness to learn CI/CD tooling (e.g. GitHub Actions), containerization (Docker), and workflow orchestration tools (Airflow/AstroCloud)
- Strong debugging and troubleshooting skills for data pipelines and ML systems
- Experience writing tests (unit, integration) and implementing monitoring/alerting for production systems
- Strong data skills, including the ability to explore and validate datasets to ensure model inputs and outputs are correct
- Basic understanding of ML lifecycle concepts and willingness to learn about model registry, versioning, and deployment practices
- Experience collaborating with Data Science teams or similar cross-functional collaboration
- Understanding of software testing and validation practices, with willingness to learn model-specific governance requirements
- Ability to participate in code reviews and learn from feedback
- Good communication skills with both technical and business stakeholders
- Eagerness to learn and grow in ML engineering and deployment practices
- (Nice to have) Any exposure to MLflow, model monitoring, or MLOps tools
- (Nice to have) Experience with data pipeline tools or frameworks
- Personal Attributes
- You're a motivated engineer who enjoys collaborative problem-solving and wants to grow your expertise in ML engineering.
- You care about code quality and are eager to learn about model deployment best practices, auditability, and production systems.
- You communicate well, ask thoughtful questions, and are excited to bridge the gap between Data Science experimentation and production-grade systems.
- You're interested in learning about deployment standards and the audit and reconciliation expectations that come with production ML.
- You're enthusiastic about contributing to automated and self-serve model deployment systems.
- You take initiative, are reliable in your commitments, and value learning from experienced team members.
- You appreciate structure and are committed to developing high standards in both technical delivery and communication.
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Machine Learning Engineer
Posted today
Job Viewed
Job Description
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.
Machine Learning Engineer
Posted today
Job Viewed
Job Description
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.
Machine Learning Engineer
Posted today
Job Viewed
Job Description
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.
Machine Learning Engineer
Posted today
Job Viewed
Job Description
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.
Machine Learning Engineer
Posted today
Job Viewed
Job Description
We’re Hiring: Data Scientist / Machine Learning Engineer
Location: Sheffield/London (hybrid)
Employment Type: Contract
We are seeking a highly skilled Data Scientist / Machine Learning Engineer to join our team. This role involves working with large datasets, applying advanced analytics, and building predictive models to drive actionable business insights.
Responsibilities:
- Preprocess structured and unstructured data for analysis
- Enhance data collection procedures to include all relevant information for analytic systems
- Process, cleanse, and validate the integrity of data
- Analyze large volumes of data to identify patterns and solutions
- Develop predictive systems and machine learning algorithms
- Present analytical results clearly to stakeholders
- Propose solutions and strategies for business challenges
- Perform data mining and extract usable insights from multiple data sources
- Use machine learning tools to select features, create, and optimize classifiers
Qualifications:
- Programming Skills: Expertise in Python; Scala/Java knowledge is an advantage
- OpenTelemetry Expertise: Strong understanding of OpenTelemetry stack (VMs, middleware like IIS/Apache, hypervisors, databases, etc.) and OTLP formatting/structuring
- Ability to correlate streaming OLTP data from multiple components and generate actionable insights using ML models
- Strong analytical and problem-solving skills
- Experience with feature selection, classifier creation, and optimization
Machine Learning Engineer
Posted today
Job Viewed
Job Description
We’re Hiring: Data Scientist / Machine Learning Engineer
Location: Sheffield/London (hybrid)
Employment Type: Contract
We are seeking a highly skilled Data Scientist / Machine Learning Engineer to join our team. This role involves working with large datasets, applying advanced analytics, and building predictive models to drive actionable business insights.
Responsibilities:
- Preprocess structured and unstructured data for analysis
- Enhance data collection procedures to include all relevant information for analytic systems
- Process, cleanse, and validate the integrity of data
- Analyze large volumes of data to identify patterns and solutions
- Develop predictive systems and machine learning algorithms
- Present analytical results clearly to stakeholders
- Propose solutions and strategies for business challenges
- Perform data mining and extract usable insights from multiple data sources
- Use machine learning tools to select features, create, and optimize classifiers
Qualifications:
- Programming Skills: Expertise in Python; Scala/Java knowledge is an advantage
- OpenTelemetry Expertise: Strong understanding of OpenTelemetry stack (VMs, middleware like IIS/Apache, hypervisors, databases, etc.) and OTLP formatting/structuring
- Ability to correlate streaming OLTP data from multiple components and generate actionable insights using ML models
- Strong analytical and problem-solving skills
- Experience with feature selection, classifier creation, and optimization
Machine Learning Engineer
Posted today
Job Viewed
Job Description
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 ( .
Snapchat ( is a camera and messaging app that connects people to their friends and the world. Every day around the globe, millions of people use Snapchat to communicate with friends, build relationships, play, and learn. No matter where you are or how you express yourself, it's always the fastest way to share a moment!
We're looking for a Machine Learning Engineer 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
+ 1+ years of research or 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 (
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About the latest Machine learning engineer Jobs in United Kingdom !
Machine Learning Engineer
Posted 19 days ago
Job Viewed
Job Description
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 (
Machine Learning Engineer
Posted today
Job Viewed
Job Description
Machine Learning Engineer
Posted 4 days ago
Job Viewed
Job Description
About the Company
You'll be joining a global leader in commercial real estate services and investment management. Known for combining deep market expertise with innovative technology, the business is committed to modernising how investment decisions are made. You'll be part of a collaborative, forward-thinking environment where your contributions will directly shape the future of real estate techno.
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