1 to 25 of 166 Machine Learning Jobs in the City of London

with our hardware. Experience: Proven track record of developing novel algorithms (papers in NeurIPS, ICML, ICLR, CVPR, or Nature/Science journals) Hardware Aware ML/Neuromorphic Computing: FPGAs, ASICs, analog computing chips, spiking neural network (hardware), edge AI Unconventional training algorithms Reservoir computing, self-constrastive learning, forward-forward … learning, evolutionary algorithms, equilibrium propagation Physics informed neural networks, or applied ML to physics problems Deep understanding of mathematics, algebra/topology - key words are latent space, intrinsic dimensionality Experience working with hardware as well is a bonus ...

drive continuous improvement Collaborate cross functionally with product, engineering, and commercial teams Mentor and elevate a high-performing team of data scientists and ML engineers Contribute to AI strategy, including developments in generative AI Experience 6–12 years’ experience in data science, currently operating at Principal level Strong grounding … machine learning fundamentals (supervised learning essential) Proven experience delivering production-grade ML solutions Strong Python and SQL skills Experience with experimentation and data-driven decision making Ability to operate as a hands-on technical leader (not pure management) Advanced degree (Master’s or PhD) in a quantitative ...

fast and accurate results • Designing and implementing agentic AI workflows powered by LLMs • Building and maintaining scalable data pipelines • Leading technical decision-making across ML and NLP projects Requirements • 8+ years of commercial engineering and/or data science experience • Experience in technical leadership or leading ML initiatives • Strong Python … programming skills • Commercial experience with machine learning • Experience working in Natural Language Processing (NLP) • Experience training ML models using TensorFlow and/or PyTorch • Experience with search databases (e.g. Elasticsearch, OpenSearch) • Experience with cloud platforms (e.g. AWS) • Willingness to work 3 days per week onsite in London Benefits ...

available £45k to £95k DoE plus 15% clearance bonus Must be willing to be full-time on-site in Central London Skills required in machine learning, GenAI, NLP, Customer Engagement/Consultancy Who are we? We are recruiting Junior, Senior and Lead Data Scientists with AI specialism … look forward to hearing from you. KEY SKILLS: Data Science/Data Scientist/AI Engineer/AI/Machine Learning/ML/NLP/GenAI/Stakeholder Engagement/Customer Engagement/AWS/Azure/Cloud/Docker/Kubernetes/CI/CD/ ...

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 … 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 ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Machine Learning Ops Engineer Role Overview Were hiring an ML Ops Engineer to own the reliability, scalability, and operational integrity of our machine-learning systems in research & production. This role sits at the intersection of data engineering and ML infrastructure: youll design and operate data pipelines … with clear SLAs, reproducibility guarantees, and observable behaviour. This is not a research role; it is a hands-on engineering role focused on making ML systems work reliably at scale. What Youll Work On ML lifecycle infrastructure Productionizing models: packaging, deployment, versioning, and rollback Designing CI/CD pipelines ...

Machine Learning Ops Engineer Role Overview Were hiring an ML Ops Engineer to own the reliability, scalability, and operational integrity of our machine-learning systems in research & production. This role sits at the intersection of data engineering and ML infrastructure: youll design and operate data pipelines ...

www.cirium.com/About the Team: Data Science Core is a key pillar of the Data Organisation. By leveraging the latest advancements in AI and ML, the team paves the way for the future of the business, providing new predictive insights for our products, and new ways of working … internal teams through AI workflows. Our projects are wide ranging, touching every part of Cirium. Our environment supports autonomy, learning, and inclusive collaboration, with an emphasis on delivery at pace. About the Role: The Senior Data Scientist will work closely with both our client-facing and Product teams ...

Contract Duration - 6 months We are looking for talented Research Engineers to join a cutting-edge AI research team focused on advancing machine learning systems and large language models. 🔍 What You’ll Do • Conduct advanced research in machine learning systems • Design tools and infrastructure for next … scale AI models and experiments • Contribute to impactful research and real-world applications ✅ What We’re Looking For • 2+ years of experience in ML, AI, recommendation systems, or related fields • Strong Python skills with frameworks like PyTorch • Experience working with large-scale AI models and datasets • Ability to translate technical ...

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. ...

Type: Full-time | Permanent Salary: Up to £120k total compensation About Us We’re an ambitious technology company using advanced Machine Learning (ML) and Natural Language Processing (NLP) to power next-generation products. Until now, our AI projects have relied on third-party engines deployed via Docker … looking for an AI Infrastructure Lead — someone with the technical depth and vision to architect, implement, and scale an environment capable of supporting multiple ML and NLP initiatives across the business. The Role As our first senior AI hire, you’ll take ownership of designing and building the foundation ...

About the Company You will own the machine learning and computer vision components of the YEO CFR SDK. This means the facial recognition model, the three-layer passive liveness detection system (software depth analysis, pixelation detection, rPPG), anti-spoofing performance, and injection attack countermeasures. You will work alongside … pulse signal in variable lighting, at varying distances, on devices with no depth sensor, at frame rates as low as 15fps. Qualifications Tools & proficiency ML Frameworks: PyTorch (expert — primary training), TFLite (expert — Android/iOS inference), CoreML (strong — iOS Neural Engine), ONNX (strong — cross-platform interop), MediaPipe (competent — Android face ...

Innovation – London-Based Roles! Are you a tech trailblazer ready to build something extraordinary from the ground up? We’re looking for AI and Machine Learning Engineers with founding-level experience to join fast-growing start-ups in London and shape the future of technology. Why This Role … Exciting: Work with high-growth, innovative start-ups at the cutting edge of AI and machine learning Hands-on impact your work will directly influence products and company direction Collaborate with founding teams bring your ideas to life and help scale global solutions Hybrid flexibility: 3 days ...

Senior Staff Machine Learning Engineer (Drug & Target Discovery) — Senior Technical Lead Ready to build the ML backbone behind next-generation human health discovery? We’re partnering on a retained search for a Senior Staff/Principal-level Machine Learning Engineer to lead the design, training … deployment of frontier ML systems across multi-omics, biomarker discovery, target discovery, genomics, and multimodal biomedical data. This is a rare opportunity to translate cutting-edge research into robust, production-grade systems that can improve how new treatments are discovered and developed. We’re looking for senior candidates with deep ...

clean, efficient, and scalable code that adheres to software engineering principles, MLOps practices, and cloud-native development. AI Solution Delivery: Own the implementation of ML pipelines, APIs, and data integration workflows. Operational Excellence: Contribute to defining reusable development patterns, enforcing coding standards, and implementing MLOps best practices that support version … processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks ...

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 ...

experienced MLOps Engineer with a strong background in DevOps, Data Science, or Machine Learning Engineering, who has hands-on experience productionising ML models. The focus of the role is building and enabling production-grade ML environments rather than model development itself. Candidates must have deep MLflow experience … real-time) with robust CI/CD Work closely with Data Scientists to transition models from experimentation to production Build scalable, secure, and reproducible ML platforms Establish best practices around: Model governance; Monitoring and retraining; Environment management Integrate with cloud and data platforms such as Databricks, and potentially AWS SageMaker ...

edge AI into real scientific impact . Responsibilities Build and deploy LLM-powered systems (RAG, agents, workflows) for scientific use Design tools that support ML scientists and researchers in their day-to-day work Work with large, messy biomedical datasets (omics, literature, clinical data) Create multi-step AI workflows that … automate research and reasoning Develop evaluation frameworks to ensure models are accurate and reliable Collaborate closely with ML engineers, data scientists, and biologists Requirements: Core: Experience building with LLMs (GPT-style models, RAG, agents, tooling) Strong Python + data/ML engineering skills Experience working with real-world data systems ...

White Collar Factory (95009), United Kingdom, London, London Engineering Manager - Software & ML About this role We are looking for a Software Engineering Manager who brings a solid foundation in modern development and some experience with Machine Learning environments . You'll lead and grow a team that builds … integrate software features that are vital to the lives of credit card consumers. Nurture Talent: Coach and nurture your engineers, including those working on ML integration to achieve their technical, business, and personal goals. Bridge the Gap: Collaborate with Product Managers and Data Scientists to ensure ML models are effectively ...

relevant industry experience. Strong expertise in deep learning, neural networks, and generative models (diffusion, GANs, transformers). Hands-on experience with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow). Advanced programming skills in Python. Solid understanding of model training, evaluation, and scaling. Strong problem-solving, analytical, and communication skills. … programming experience (CUDA, Triton, or similar). Track record of publications at top-tier venues (NeurIPS, CVPR, ICML, ICLR, SIGGRAPH, ECCV). Experience integrating ML models into production pipelines (e.g., graphics, AR/VR, simulation systems). Contributions to open-source projects or collaboration with research labs. Key Responsibilities Develop ...

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 ...

corporate development experience to design, build, and deploy AI‐driven solutions across the deal lifecycle. This role sits at the intersection of advanced machine learning, data engineering, and strategic transactions , supporting high‐impact decisions during acquisitions, integrations, and divestments. You will work closely with investment teams, corporate development … teams to apply AI to due diligence, valuation, synergy modelling, risk analysis, and post‐merger integration. Key Responsibilities Design, build, and deploy AI/ML models to support M&A activities, including: Due diligence automation (financial, commercial, operational, and legal) Target screening and opportunity identification Risk detection and anomaly analysis ...