1 to 25 of 157 Machine Learning Jobs in the City of London

Senior Machine Learning Scientist A fantastic opportunity for a Senior Machine Learning Scientist to work for a health-tech software company developing advanced machine learning models used within clinical research. The organisation applies modern machine learning techniques to complex medical datasets … Scientist/Machine Learning Researcher/AI Research Scientist/Computer Vision Scientist/Deep Learning Scientist/AI Scientist/ML Research Engineer/Python/PyTorch/Deep Learning/Computer Vision/3D Imaging/Volumetric Imaging/Self-Supervised Learning/ ...

access services quickly and safely. Our Applied Scientist team consists of about twenty machine learning scientists. The team is supported by an ML Ops team that provides state-of-the-art tooling (including AWS, Encord, Ray, PyTorch Lightning and Weights & Biases). The Applied Science team works closely … Have strong experience in machine learning and computer vision. Have a strong record of successfully delivering high-performance ML-driven products. Have a deep understanding of machine learning theory. Have strong coding skills in Python and PyTorch. Care about building fair and cutting-edge machine ...

Machine Learning Engineer/Junior Machine Learning Engineer Level: Junior ML Engineer (£56,000) | ML Engineer (£65,000) Location: London About the Role Our client is a global defence, security, and intelligence consultancy delivering high-assurance digital, cyber, and AI solutions into some … wider government environments. The work spans exploratory research, rapid prototyping, and full production deployment. You will be solving complex, real-world problems using modern ML and LLM techniques, working on sensitive, high-impact systems where quality, governance, and operational readiness genuinely matter. What You’ll Be Doing Designing and developing ...

Machine Learning Engineer, you’ll work closely with Data Scientists, Data Engineers and delivery teams to productionise models and build robust, scalable ML systems within client environments. This role is highly hands-on, with a strong focus on deployment, performance and reliability. Key Responsibilities Translating data science models … into scalable, production-ready machine learning solutions. Designing and building end-to-end ML pipelines, from data ingestion to deployment and monitoring. Collaborating with data engineers on data architecture, pipelines and feature stores. Working closely with data scientists to productionise models and improve performance. Deploying, monitoring and maintaining ...

years’ commercial experience in Machine Learning Strong experience in Computer Vision (e.g. object detection, image classification, segmentation) Experience building, training and optimising ML models Python (NumPy, Pandas, scikit-learn) and frameworks such as TensorFlow or PyTorch Experience deploying models into production environments (cloud platforms, Docker, CI/… resided in the UK continuously for the last 5 years) These roles offer the opportunity to work on impactful, real-world projects where robust ML solutions are critical. If you’re exploring new contract opportunities and meet the above criteria, please apply or drop me a direct message. ...

with large, complex datasets to support AI-driven products and insights 🧠 Assist with feature engineering, model experimentation, and performance optimisation ☁️ Contribute to data and ML pipelines in cloud-based environments 🗄 Work with structured and semi-structured data using SQL 🚀 Support the deployment and monitoring of models in production environments 🤝 Collaborate … years of experience in AI, machine learning, or software/data engineering (including internships, placements, or academic projects) 🐍 Strong Python skills for ML and data processing 🗄 Experience working with SQL and structured datasets ☁️ Familiarity with cloud platforms and modern data stacks 🧠 A solid understanding of machine learning ...

engineering environment. Required: Core experience Strong grounding in audio machine learning or applied signal processing Experience training and evaluating models using modern ML tooling Awareness of real-world acoustic challenges such as noise, reverberation, and variability Comfort working in a small, fast-moving engineering team Likely … + some industry experience Beneficial Edge or embedded ML optimisation Audio feature extraction or DSP knowledge Postgraduate study in a relevant technical discipline Experience with sensing, monitoring, or real-world data systems ...

this role! You'll help lead and implement the improvement of algorithms, optimising execution, usability, and package architecture of our ML Verification packages. Note that this is a Python code focused role, rather than a Data Science role, so Python programming skills are the priority, where as Machine Learning … systems we build are safe to use. To meet this need, we are developing advanced deep validation techniques and tools that allow AI/ML engineers world-wide to validate the robustness of their models, as well as repair the fragilities that they discover. By joining ...

client is looking for an experienced ML Infrastructure Engineer to support the deployment, optimisation and scaling of advanced machine learning models in production environments. This role sits at the intersection of research and engineering, focused on ensuring models are reliably transitioned from experimentation through to large-scale deployment. … improve deployment efficiency and platform scalability Evaluate and integrate third-party infrastructure and inference tooling where appropriate Requirements Proven experience deploying and maintaining ML inference systems in production environments Strong programming experience in Python and familiarity with modern machine learning frameworks Experience working with containerisation and orchestration technologies ...

preparing data from multiple sources Designing and implementing data models and algorithms to address business challenges Building, testing, and deploying predictive analytics and machine learning solutions Visualising data and communicating insights clearly to technical and non-technical stakeholders Ensuring data integrity, security, and compliance with internal policies … related discipline Strong proficiency in Python or R for data analysis Experience working with SQL and relational databases Proven experience building and deploying machine learning models Desirable Experience using a major cloud platform Exposure to big data technologies (e.g. distributed data processing frameworks) Experience with data visualisation tools ...

developing advanced autonomous systems is looking for an AI Developer to join its growing team in London. This role sits at the intersection of machine learning and robotics, focused on building intelligent decision-making and control systems for real-world platforms. You’ll be working closely with engineers … researchers to develop AI that operates reliably in complex, changing environments. The Role You’ll be responsible for designing and implementing probabilistic and machine learning models that support navigation, planning and adaptive control. A key part of the position will involve integrating these models into real robotic systems ...

Machine Learning Engineer Full Time London - Hybrid Were partnering with a rapidly scaling PropTech SaaS business transforming how property … data is enriched, automated, and delivered across multi-tenant environments. Theyre now hiring a Machine Learning Engineerto help build intelligent, production-grade ML systems at the core of their platform click apply for full job details ...

Engineer with strong software engineering fundamentals to join our team of domain experts and researchers. You will be responsible for building robust, scalable ML systems that bring our foundation models for retail from prototype to production. Key Responsibilities Design and build production-grade ML infrastructure, including training pipelines, model … serving, and monitoring systems. Collaborate with research engineers to translate experimental models into reliable, maintainable software. Optimise ML systems for performance, scalability, and cost-efficiency in cloud environments (distributed clusters, GPUs). Establish engineering best practices for ML development, including testing, CI/CD, and code review standards. Progression Timeline ...

Role Our client is looking for a Machine Learning Engineer to join their Spacetime team. This is a hybrid role combining ML research and engineering, focused on solving some of the most complex temporospatial networking and resource management problems in the industry. Youll work at the cutting edge … driven networking and space systems, collaborating with engineers, researchers, and customers globally. Key Responsibilities Research and develop state-of-the-art ML algorithms for network orchestration Build and manage ML training infrastructure using Kubernetes and MLOps tools Develop and maintain documentation for new algorithms and systems Integrate AI/ML ...

deliver high-impact, data-driven solutions. Key Responsibilities Develop data pipelines , machine learning , and optimisation models in Python Build and industrialise ML/optimisation algorithms using best-practice software engineering principles Implement automated data cleaning pipelines and workflow orchestration (e.g. Dagster) Integrate ML/optimisation models into full … techniques (Regression, Tree methods, Clustering, Linear/Mixed-Integer Programming, Heuristics) Strong Python experience (scikit-learn, pandas, numpy, optimisation libraries) Experience building production-ready ML or optimisation solutions Solid understanding of CI/CD , Git version control, and cloud platforms ( AWS preferred ) Strong data engineering skills in Python ...

developers and researchers. 🛠️ Skills and Experience 5+ years of experience in software engineering, with a strong focus on AI and Machine Learning (ML). Expert-level proficiency in Python and deep learning frameworks, particularly PyTorch. Proven experience building and deploying applications with LLM APIs such as OpenAI … 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. ...

that push the boundaries of AI integration in cloud services. Thought Leadership and Client Engagement • Provide architectural guidance to clients on incorporating GenAI and machine learning into their cloud[1]native applications and architectures. • Conduct workshops, briefings, and strategic dialogues to educate clients on AI benefits and applications … development. • Technologies: Proficiency in Python, Java (and/or Golang), and Spring; expertise in AWS, Azure, Google Cloud; Kubernetes and containerization. • AI Expertise: Advanced machine learning algorithms, GenAI models (e.g., GPT, BERT, DALL-E, GEMINI), NLP techniques. • Big Data: Experience with Hadoop and Spark. • Ethics: Knowledge ...

deliver real products used by investment teams and portfolio companies. This role is ideal for: PhD graduates in a STEM field with applied ML, optimization, or computational experience; or Bachelor’s/Master’s graduates with 1–2 years of industry experience or relevant internships in machine learning, data engineering, or software engineering. You’ll contribute to designing, implementing, and deploying production-grade ML systems—ranging from NLP pipelines to model‐driven workflow automation. You’ll learn quickly, gain real ownership, and see your work make tangible business impact. What You’ll Do Build and deliver ML ...

creator ecosystem, and developing models for strategic content valuation. Multi-objective balancing and long term measurement. We rely extensively on state-of-the-art ML around personalization, deep learning, causal inference, optimization, ranking and recommendation. What You’ll Do Within the Sharechat AI team, we are looking … engagement while minimizing server and cloud costs of serving large scale models, and act as a subject matter expert in the recommender systems and ML ranking domains. You would be joining us at an exciting time! The science behind recommendation systems is rapidly changing, and we’re making big progress ...

AI. Conduct exploratory analysis to understand user behavior, discover optimization opportunities, and develop behavior models to inform product enhancements. Design and deploy data/ML instrumentation to extract insights and optimize the product experience. Provide strategic product guidance through data-driven recommendations, experimentation insights, and root cause analyses. Build … implement, and monitor key performance metrics for AI-driven product features. Stay up to date with industry advancements in data processing and AI/ML, and introduce best practices into the organization. Requirements 7+ years of experience in data science, machine learning, and AI development across structured ...

analysts, coaches, and performance staff to understand requirements and translate them into actionable data solutions Stay up to date with advancements in sports analytics, machine learning, and data science methodologies Your Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python … Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models ...

alternative data, ensuring absolute consistency for research teams. Operationalize Machine Learning: Bridge the gap between research and production by deploying complex ML models into live environments under strict latency constraints. Optimize the Stack: Go "close to the metal" to optimize performance across networking, I/O, and compute … Have Polyglot Mastery: Exceptional command of at least one major systems language ( C++ , Rust , Java ) for low-latency components, or Python for data and ML workflows. Distributed Systems Expertise: Deep experience building high-throughput, fault-tolerant systems using modern messaging standards (e.g., Kafka , ZeroMQ , NATS ). Systems-Level Intuition ...

communication Other: Mapping/location-based services There’s also scope to get involved in machine learning over time. Staxy already use ML to process GPS data and understand travel behaviour, and this will become a bigger focus as the platform evolves. You don’t need ML experience … React Native/Expo experience MongoDB Fastify or similar Node frameworks Mapping or location-based services Payments (e.g. Stripe) Any exposure or interest in machine learning Growth & progression Because the team is small and early-stage, this is a role where progression is earned, not capped. As Staxy ...

code reviews to ensure robust contributions like suggesting extra tests, spotting inconsistencies and helping resolve problems. The Player A postgraduate qualification in Data Science, Machine Learning, Statistics, Mathematics or a closely related quantitative field. 3+ years of working experience or a PhD in a quantitative field. Advanced programming … models for sports. A good understanding of betting concepts and markets. Desirable Qualifications 2+ years working experience in the betting industry. Knowledge of modern Machine Learning methodologies (e.g. Neural Networks, Random Forests, GBMs, SVMs etc.). Experience with cloud computing services. Experience with version control platforms (e.g. GitHub ...

models. Strategic Workflows: Develop enterprise-grade workflows and decision-support tools that reshape operations across industries. AI Leadership: Guide the integration of AI and machine learning models into client environments, ensuring measurable outcomes. Client Engagement: Partner directly with senior stakeholders, translate business needs into technical solutions, and influence … workflow design at enterprise scale. Track record of leading teams, mentoring engineers, and delivering complex projects in client-facing environments. Passion for AI, machine learning, and emerging technologies, with ability to translate innovation into impact. Exceptional problem-solving, communication, and stakeholder management skills. Curiosity, adaptability, and a drive ...