233 Senior Machine Learning Engineer jobs in London
Machine Learning Engineer
London, London
Experis
Posted today
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Job Description
We are seeking a highly skilled Machine Learning Engineer to join our team on a contract basis. You will be responsible for designing, building, and deploying machine learning models into production, working closely with data scientists, software engineers, and product teams to deliver scalable AI solutions. This is an excellent opportunity for someone who thrives in fast-paced environments and enjoys solving complex problems with real-world impact. Key Responsibilities Develop, train, and optimize machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure seamless integration of ML models into products. Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow). Proficiency in working with cloud services (AWS, GCP, or Azure). Strong understanding of CI/CD, containerisation (Docker), and orchestration (Kubernetes). Excellent problem-solving skills and ability to work independently in a fast-paced environment. Desirable: Experience with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience
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0
Machine Learning Engineer
London, London
Experis
Posted today
Job Viewed
Job Description
We are seeking a highly skilled Machine Learning Engineer to join our team on a contract basis. You will be responsible for designing, building, and deploying machine learning models into production, working closely with data scientists, software engineers, and product teams to deliver scalable AI solutions. This is an excellent opportunity for someone who thrives in fast-paced environments and enjoys solving complex problems with real-world impact. Key Responsibilities Develop, train, and optimize machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure seamless integration of ML models into products. Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow). Proficiency in working with cloud services (AWS, GCP, or Azure). Strong understanding of CI/CD, containerisation (Docker), and orchestration (Kubernetes). Excellent problem-solving skills and ability to work independently in a fast-paced environment. Desirable: Experience with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience
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1
Machine Learning Engineer
London, London
Experis UK
Posted today
Job Viewed
Job Description
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.
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2
Machine Learning Engineer
London, London
Experis UK
Posted today
Job Viewed
Job Description
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.
This advertiser has chosen not to accept applicants from your region.
3
Machine Learning Engineer
London, London
Experis
Posted today
Job Viewed
Job Description
We are seeking a highly skilled Machine Learning Engineer to join our team on a contract basis. You will be responsible for designing, building, and deploying machine learning models into production, working closely with data scientists, software engineers, and product teams to deliver scalable AI solutions. This is an excellent opportunity for someone who thrives in fast-paced environments and enjoys solving complex problems with real-world impact.
Key Responsibilities
- Develop, train, and optimize machine learning models for production use.
- Collaborate with data scientists to turn research prototypes into production-grade solutions.
- Build robust data pipelines and feature engineering workflows.
- Deploy ML solutions into cloud environments (AWS, GCP, or Azure).
- Implement monitoring, testing, and model performance evaluation frameworks.
- Work with engineering teams to ensure seamless integration of ML models into products.
- Contribute to improving infrastructure, tooling, and best practices for ML development and deployment.
Skills & Experience
Essential:
- Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn).
- Proven experience in developing and deploying machine learning models in production.
- Solid understanding of data structures, algorithms, and software engineering principles.
- Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow).
- Proficiency in working with cloud services (AWS, GCP, or Azure).
- Strong understanding of CI/CD, containerisation (Docker), and orchestration (Kubernetes).
- Excellent problem-solving skills and ability to work independently in a fast-paced environment.
Desirable:
- Experience with NLP, computer vision, or time-series forecasting.
- Familiarity with distributed computing frameworks (Spark, Ray).
- Experience with MLOps and model governance practices.
- Previous contract experience in a similar ML engineering role.
Contract Details
- Duration: 6–12 months (extension possible)
- Location: London (Hybrid working model)
- Day Rate: Competitive, depending on experience
This advertiser has chosen not to accept applicants from your region.
4
Machine Learning Engineer
London, London
Acceler8 Talent
Posted today
Job Viewed
Job Description
Machine Learning Engineer | Scalable AI Systems A fast-growing AI scale up is building the next generation of intelligent, high-performance systems - combining machine learning and systems optimization to power real-world applications at scale. As an ML Engineer , you’ll take models from idea to production - implementing, optimizing, and scaling them to handle massive workloads efficiently. You will be collaborating closely with other engineers to build AI systems that are reliable, maintainable, and ready for real-world deployment . What you’ll do: • Develop, deploy, and optimize ML models for production use • Integrate & monitor AI pipelines with engineering teams • Ensure models are efficient, scalable, & aligned with product goals If you’re excited to engineer AI systems that truly scale , this is your chance to make a meaningful impact.
This advertiser has chosen not to accept applicants from your region.
5
Machine Learning Engineer
London, London
SGI
Posted today
Job Viewed
Job Description
Machine learning Quantitative Engineer London - Hybrid working Rate - £1,200 Key Responsibilities Research, design, and implement machine learning and quantitative models for pricing, trading signals, and risk management across Fixed Income products (rates, credit, FX, mortgages). Apply advanced statistical learning methods (time-series, NLP, deep learning, reinforcement learning, graph-based models) to large-scale, high-frequency, and alternative datasets. Engineer robust data pipelines and real-time model deployment frameworks to support production trading environments. Collaborate with traders, quants, and technologists to prototype and scale strategies from research to execution. Conduct rigorous backtesting, performance analysis, and explainability assessments of machine learning models. Contribute to the development of quantitative libraries and shared research infrastructure. Qualifications & Skills Essential: Strong expertise in machine learning, statistical modelling, and numerical methods with practical applications. Proficiency in Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) and experience with C++ or Java for high-performance model integration. Solid understanding of Fixed Income products, yield curve modelling, and financial mathematics. Experience building production-level ML systems in low-latency or large-scale environments. Strong communication skills with the ability to interact effectively with both technical and trading stakeholders. Desirable: Previous front-office or systematic trading desk experience. Familiarity with modern MLOps (Docker, Kubernetes, MLflow, Airflow) and distributed computing (Spark, Ray). Experience with alpha signal generation, regime detection, or portfolio optimization. Exposure to alternative/ESG datasets, macroeconomic indicators, and sentiment analysis.
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6
Machine Learning Engineer
London, London
Digital Waffle
Posted today
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Job Description
An AI-driven start-up, backed by $20M in Series A funding, is looking for its first Machine Learning Engineer to help scale their product and infrastructure. The platform transforms educational content into smart, personalised learning tools - and is already seeing rapid user growth and strong traction in the market. This is a unique opportunity to join early, influence the technical roadmap, and work directly with experienced founders and a senior engineering team. What you’ll be doing: Designing, building and deploying ML-powered features across a production platform Working across Python and TypeScript , integrating models into scalable, real-time systems Fine-tuning and training NLP models using techniques like transformers Driving the machine learning strategy and building best practices from the ground up Collaborating closely with product, engineering, and leadership What we’re looking for: Strong commercial experience building and deploying ML models in production Proficiency in Python and familiarity with TypeScript/JavaScript Experience with NLP or recommendation systems is a bonus Excited by start-ups: product-minded, hands-on, and motivated by impact What’s on offer: £100,000 - £120,000 salary meaningful equity 4 days/week in a modern London office near Liverpool St Greenfield ML ownership with direct access to founding team A chance to shape the future of an AI product already loved by users
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7
Machine Learning Engineer
London, London
Montash
Posted today
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Job Description
Machine Learning Engineer | Generative AI | AWS | End-to-End ML Solutions Location: London-based | Hybrid Please note: Sponsorship is not offered for this position We’re working with a leading organisation on a mission to become one of the most insight-driven businesses in its sector, placing machine learning and generative AI at the core of customer experiences, operational optimisation, and strategic decision-making. This is a fantastic opportunity for a skilled Machine Learning Engineer to build and deploy scalable, production-level ML solutions, working closely with Data Scientists and cross-functional teams to drive measurable business impact. You’ll play a pivotal role in integrating machine learning models into end-to-end pipelines, supporting strategic initiatives such as customer engagement, automated insights, and decision-support tooling. You’ll also contribute to shaping the frameworks, infrastructure, and shared tooling that enable safe, responsible, and efficient AI experimentation and deployment. If you’re passionate about problem-solving, applying ML to real-world challenges, and bringing ideas to life in production environments, this role is a great fit. What You’ll Be Doing Machine Learning Engineering Build, deploy, and maintain ML models as services, streaming applications, or batch jobs across real-time and offline platforms. Develop scalable model APIs with strong CI/CD and observability practices. Implement model testing, monitoring, and rollback capabilities in production environments. Collaborate with Data Scientists to translate prototypes into reliable, maintainable ML applications. Identify opportunities to develop new ML solutions in partnership with Data Science teams. Platform & Tooling Automate and standardise ML infrastructure using Docker, Kubernetes, and Terraform. Support and develop monitoring dashboards for key ML and AI services. Ensure cloud-native, secure, and cost-efficient deployments in AWS environments. Contribute to the development of shared platforms and tooling that enable model deployment and experimentation. Compliance Adhere to governance, risk, and compliance obligations relevant to the role. Identify and escalate non-compliance issues when necessary. Proactively challenge processes that may impact compliance standards. Complete all mandatory compliance training and engage with compliance teams for clarification when needed. What You’ll Bring 3–5 years of experience in machine learning engineering and data science. Advanced degree (PhD or Master’s) in a numerate discipline. Excellent programming skills in Java and Python for production systems. Strong foundations in machine learning and data science. Experience deploying ML models as APIs, batch jobs, or streaming services (e.g., Kafka Streams). Proficiency in containerised application deployment with Kubernetes. Demonstrated experience building ML solutions from concept to delivery. Strong cloud engineering skills (AWS preferred; Terraform or CloudFormation a plus). Excellent communication and collaboration skills. Up-to-date knowledge of modern ML and AI developments. Why Join This is a chance to work on impactful machine learning use cases that shape the future of customer experiences and business operations. You’ll be part of a collaborative environment where innovation is encouraged, and you’ll have the autonomy to influence tooling, frameworks, and production ML strategy. Please note: Sponsorship is not offered for this position. Candidates must have the existing right to work in the relevant location.
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8
Machine Learning Engineer
London, London
Intellect Group
Posted today
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Job Description
Are you a Machine Learning Engineer ready to kickstart your career in AI? We’re looking for a driven and detail-oriented Machine Learning Engineer to join our hybrid-working team in London. You’ll collaborate with talented engineers and data scientists to build and deploy intelligent systems that transform unstructured data into actionable insight. You’ll be joining a fast-growing AI company developing automation solutions that extract meaning from emails, documents, and other unstructured communications — turning them into structured data and insights that drive real business decisions. Our technology powers next-generation AI workflows for enterprise clients across sectors like finance and professional services. This is an exciting opportunity for a recent graduate or early-career professional with up to one year of experience who’s passionate about machine learning, generative AI, and applying cutting-edge research to real-world challenges. In this role, you’ll: Design, train, and evaluate machine learning and deep learning models for production environments Develop and optimise end-to-end ML pipelines — from data preparation to model deployment Experiment with advanced generative and predictive models , including diffusion, autoregressive, and transformer-based architectures Collaborate with data engineers and software developers to integrate AI solutions into scalable systems Contribute to research and experimentation around model performance, optimisation, and privacy-aware learning What’s in it for you? Career Growth – Build hands-on experience in cutting-edge AI while developing your technical expertise through mentorship and ongoing learning Impactful Work – Contribute to real-world projects where your models and insights directly shape intelligent products Collaborative Environment – Join a supportive, curious, and innovative team that values experimentation and creative problem-solving Hybrid Flexibility – Balance remote focus time with in-person collaboration at our London office Learning Pathway – Gain exposure to advanced ML frameworks and progress toward senior engineering roles as you grow What We’re Looking For: A degree in Artificial Intelligence, Computer Science, Mathematics, or a related field Proficiency in Python and experience with frameworks such as PyTorch , NumPy , or Scikit-learn Understanding of machine learning algorithms, optimisation, and model evaluation Strong mathematical reasoning and analytical problem-solving skills Excellent communication skills and a genuine passion for learning and innovation Nice to Have: Experience with JAX , Hydra , or Weights & Biases Exposure to GANs , diffusion models , or autoregressive architectures Knowledge of data privacy , machine unlearning , or secure ML methods Internship or academic project experience in AI research , data science , or software development If you’re ready to take your first step into applied machine learning and work on projects that push the boundaries of AI innovation — we’d love to hear from you. Apply now and be part of shaping the future of intelligent automation!
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