1 to 25 of 36 Machine Learning Jobs in Bedford

seeking an experienced Machine Learning Engineer to support a Financial Services organisation on an initial 6-month contract, working on production-grade ML systems that operate in regulated, high-volume environments. This role is ideal for someone comfortable taking models from research through to deployment, with a strong … into production within a Financial Services environment Collaborate closely with Data Scientists, Software Engineers, Risk, and Product teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support ...

looking for an experienced Senior Machine Learning Engineer to lead the design and production integration of ML into an established live trading system and drive its next phase of development. Building on our early ML research and prototypes, you will design, build, deploy, and operate production ML components … making and execution quality with measurable financial impact. This is an excellent opportunity for someone who enjoys autonomy, technical responsibility, and building production-grade ML systems where reliability, latency, and real-world feedback loops matter. What You'll Do Lead the design and production integration of ML components into ...

most value. This role combines hands-on technical work with the opportunity to influence strategy, tooling and ways of working, particularly around AI and ML adoption. You'll be involved across the full lifecycle, from problem definition and experimentation through to deployment, governance and ongoing optimisation. What … data team Collaborating with Product and Engineering on strategic AI-driven initiatives Identifying and developing high-impact use cases for data science and ML Helping define ML lifecycle standards, documentation and governance Communicating insights and model outputs clearly to technical and non-technical stakeholders What we're looking for Essential ...

Permanent Remuneration (UK – Remote): £81–108k Base Salary + Discretionary Bonus + Equity We are a stealth-mode AI laboratory researching and developing Machine Learning models. The founding team consists of Cambridge graduates and former engineers at Google, Meta, Bloomberg, Microsoft and Amazon. We are backed by prominent … institutional VC funds and C-level executives of global technology companies. The role involves the design and development of backend services and infrastructure for Machine Learning workloads. You will be working closely with the Machine Learning team; however, you are not required or expected to have ...

seeking a hands-on Machine Learning Senior Staff Engineer to lead cross-functional teams building and deploying cutting-edge LLM and ML systems. In this role, you'll drive the full lifecycle of AI development — from research and large-scale model training to production deployment — while mentoring … that break the models and navigating the intersection of research, engineering, and product delivery. Roles & Responsibilities: Lead and mentor a cross-functional team of ML engineers, data scientists, and MLOps professionals. Oversee the full lifecycle of LLM and ML projects — from data collection to training, evaluation, and deployment. Collaborate with ...

limit and you'll help us get there. Key Responsibilities Stay up to date with the state-of-the-art in Artificial Intelligence and Machine Learning, and apply it to the problem of Enterprise Vibe Coding; Make use of techniques such as In-Context Learning (Prompt Engineering … practice in a large-scale project. Qualifications/What You Need To Succeed Ph.D. or MSc degree in Computer Science, Electrical Engineering, Artificial Intelligence, Machine Learning, or related technical fields is highly valued. 7+ years of work experience in Machine Learning and AI Engineering roles, preferably ...

with speed, accuracy, and control, gearing up for 4x growth in 2026, it has never been a more exciting time to join! As Senior ML Engineer, you'll build the production systems that make this possible, ingestion pipelines, graph-based orchestration, and integration of NLP, LLMs, and ML components into … take full ownership of projects, shape the technical direction from the ground up, and grow your career. Stack: Python, API design, Neo4j, Graph schemas, ML/LLM integration/deployment What do you need? Strong backend engineering experience with Python Experience building production ML/NLP systems/deploying ...

Senior Machine Learning Engineer An Agentic AI start up looking for a Senior Engineer (AI/ML focused) to join them! They are a small high performing team. After building an Agentic AI platform they are now becoming hyper focused on a niche and fine-tuning their models. … join them as they become super specialized and break into a new market The role: You'd be coming on board to integrate ML and NLP components into real-world workflows Focus on turning modelling logic into scalable, reliable workflows Build and operate the systems that power their agentic platform ...

Machine Learning, Python, TensorFlow, PyTorch, scikit-learn, Large Language Models, LLM, Data preprocessing, REST API, Microservices architecture, MLOps, CI/CD for ML, Power-BI, Docker, Kubernetes, AI Ethics, Cloud Platforms, AWS, Google Cloud Platform, SQL, NoSQL, DevOps, Financial services, Regulatory environments Contract Type: Hybrid/Bedford Daily … data preprocessing, feature engineering, and model evaluation. Develop and maintain REST APIs and microservices architectures. Monitor, evaluate, and apply governance frameworks for AI/ML models in production environments. Prepare technical documentation and effectively communicate complex concepts to both technical and non-technical stakeholders. Required Skills & Qualifications: Minimum 2 years ...

Financial Crime, Data & AI-driven SaaS company helping organisations detect, prevent, and manage financial crime at scale. Our platform combines advanced data, AI and machine learning to deliver market-leading solutions across: Financial Crime Risk Management Anti-Money Laundering (AML) & Counter-Terrorist Financing (CTF) KYC & Risk Assessment Watchlist … from anywhere Competitive base salary + uncapped commission High-growth SaaS business in a mission-critical market Opportunity to sell cutting-edge AI and machine learning technology Clear career progression and leadership opportunities Collaborative, ambitious, and supportive culture ...

technologies, libraries, and tools where appropriate. AI & Automation: Integrate AI and machine-learning powered features into backend systems. Collaborate with AI/ML specialists to deploy and maintain intelligent services. Stay up to date with emerging AI trends and identify opportunities for automation and optimisation. Qualifications 5+ years … . Strong understanding of cloud platforms (AWS, Azure, or GCP). Experience mentoring junior developers or leading small development teams. Familiarity with AI/ML frameworks, data pipelines, or integrating large language models/APIs. Strong problem-solving skills and the ability to translate complex requirements into scalable solutions. Excellent ...

Replit, Bolt • APIs & Microservices: RESTful APIs, GraphQL, microservice architectures • Cloud & DevOps: AWS, Azure, or GCP; Docker; CI/CD pipelines • Data Integration: Products integrating ML/AI models, databases, BI tools • UI/UX Awareness: Collaborate on interfaces, data visualisation, user journeys • Other: Version control (Git/GitHub), testing frameworks … facing products • Proven experience in rapid prototyping, innovation labs, or product R&D teams • Commercial experience with AI enabled products using GenAI (LLMs) or Machine Learning • Familiarity with compliance, retail, FMCG, or operational intelligence systems (advantageous) • Prior startup or SME experience where engineers own end-to-end delivery ...

cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling and optimisation. Calculus for optimising algorithms and models. Predictive modelling techniques … regression and classification. Time series analysis for handling time-dependant data. Deep learning and neural networks. LLM Operations Expertise in managing and operationalising large language models. Experience in deploying models on cloud platforms (e.g. AWS, Sage maker, Google AI Platform, IBM Watson ...

, data science, and scientific discovery. Our teams work at the intersection of cloud infrastructure, high-performance computing, and data engineering, enabling researchers and ML practitioners to move faster—from experimentation to real-world impact. This role sits at the heart of the platform: designing, scaling, and operating systems that … This Role Is For (Choose Your Strength) We're open to different profiles and will shape the role around your strengths: AI Platform/ML Infrastructure Engineers Kubernetes-based compute platforms GPU scheduling, batch & distributed workloads Supporting ML training, inference, and experimentation at scale HPC/GPU Engineers Job schedulers ...

ML Platform Engineering Manager – AI Infrastructure Central London (3 days on-site) | Full-time We're an AI-first technology company building tools that help people and brands create beautiful visual content at scale. Our products are powered by cutting-edge machine learning and used by millions worldwide … just getting started. We're now looking for an ML Platform Engineering Manager to lead the team responsible for the infrastructure behind our AI models. This is a hands-on leadership role at the intersection of engineering, research, and product—perfect for someone who loves solving complex systems problems ...

research into production pipelines Help set technical direction and best practices for AI-driven interaction work Required experience Strong experience working with AI/machine learning systems (research and/or applied) Deep experience in one or more of the following: Human motion generation … Character animation or character control, Emotion recognition or affective computing, Human pose estimation, Virtual humans or embodied AI Strong proficiency in Python and modern ML frameworks (e.g. PyTorch) Proven ability to translate research ideas into working systems Track record of technical ownership and independent problem-solving Creative, research-driven mindset ...

self-funded, independent AI group, focused on building a new consumer AI application with global impact. We're assembling a small, elite team of ML, engineering and product builders who want to work on meaningful, high-impact problems. About The Role You will shape the core technical direction … zero-to-one technical problems end-to-end Nice to Have Experience with LLM inference frameworks (vLLM, TensorRT-LLM, FasterTransformer) Contributions to open-source ML libraries Background in scientific computing, compilers, or GPU kernels Experience with RLHF pipelines (PPO, DPO, ORPO) Experience training or deploying multimodal or diffusion models Experience ...

/requirements 4. Experience with cloud/server management (AWS, Azure, or local hosting). 5. Knowledge of cybersecurity best practices. 6. Familiarity with machine learning frameworks (e.g. TensorFlow, PyTorch). 7. Previous leadership or mentoring experience. NB. You would be expected to work 4 days a week ...

omnichannel support. Automate deployments via AWS CodeBuild, Jenkins, and Ansible; manage VPCs, RDS, and Elastic Beanstalk for Flex workloads. Enhance Flex with AI/ML integrations (e.g., AWS Lex, SageMaker) and performance tuning for global scale. Lead troubleshooting, security audits (IAM, GuardDuty), and cost optimization in dynamic environments. Requirements: 5+ ...

scalable, secure, reliable, and enterprise-ready. Key Responsibilities Own the full platform architecture, including ingestion, scoring, data stores, APIs, and dashboards. Lead AI/ML-powered enrichment and scoring systems. Build and scale microservices, event-driven pipelines, and automated intelligence workflows. Harden cloud infrastructure and implement security, compliance ...

growing market with meaningful impact and long-term upside What You Bring 5+ years of experience in enterprise or strategic sales, ideally within AI, ML, security, or technical services Proven ability to close complex, high-value deals with technical customers Experience selling consultative, services-led offerings rather than purely transactional ...

Celery, Sidekiq, Resque, SQS, etc.) Experience with observability stacks (e.g., Datadog, Prometheus, Grafana, Sentry) Strong Python skills Nice to haves Experience supporting AI/ML workloads in production Background in offensive security, CTFs, or security research ...

Postgres databases Experience with modern front-end development (TypeScript/React) Excellent written communication — clear, structured, and precise Nice to haves Publications at leading ML venues (e.g. NeurIPS, ICLR, ICML) or related research areas Familiarity with common LLM evaluation tooling (e.g. OpenAI Evals or similar frameworks ...

Process: Intro call where we talk about the role. Technical discussion with the Head of AI. Deep-dive session with a Backend Engineer and ML Engineer from the team. 30-minute conversation with the Founder. Why This Is Worth Your Time Real ownership: You'll be the architect behind ...

weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers, Solution Architect, and domain experts from Admissions, Registry and Student Services. Design experiments, test hypotheses, and iterate quickly, ensuring human-in-the-loop … with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g., orchestration, RAG services, prompt safety, connectors) that support multiple domains such ...