14 of 14 Remote/Hybrid Machine Learning Jobs in Bedford

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 ...

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 ...

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 ...

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 ...

/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 ...

experimentation, balanced by enterprise-grade governance, technical rigour and operational discipline. We want to hear from you if: Have led an applied AI or ML function, owning product direction and technical strategy for enterprise-grade AI platforms. Have operated as an AI Engineer or AI Architect at at Staff/ ...

direct impact on the business, working closely with the founders and leadership team. What You'll Do: Design, build, and deploy AI/ML models powering the core platform. Create scalable AI infrastructure, data pipelines, and deployment workflows. Collaborate with product and engineering to turn business problems into AI solutions. … Experiment with the latest AI techniques to innovate and deliver real-world impact. Mentor future AI/ML hires as the team grows. What We're Looking For: Proven experience in AI/ML, ideally from a startup or high-growth scaleup environment. Expert in Python and frameworks such ...

with rapid commercial traction across top UK & US firms, they are scaling fast and this is the time to join. The Role: AI/ML Engineer – Agentic Systems You will design and deliver intelligent agentic workflows, leveraging frontier LLMs. Working with their data scientists and backend engineers … roadmap for intelligent systems and ensuring scalability, compliance, and robustness. Requirements Strong programming experience with Python. Proven track record building production-grade AI/ML systems (emphasis on implementation and integration over pure research). Practical experience with AWS (and ideally Terraform, GitLab CI). Experience with agentic systems ...

based health and wellbeing organisation is hiring a Data Scientist to build and deploy production ML and GenAI systems. The role is hands-on and end to end, covering data preparation, model development, and deployment across traditional ML and LLM-based use cases. You will work on real production problems … through to live deployment. You will collaborate closely with other data scientists, data engineers, and DevOps, with the freedom to shape how GenAI and ML are used across the platform. Tech stack: Python PyTorch or TensorFlow scikit-learn Spark Kafka Databricks LangChain and RAG-based GenAI systems Cloud-native Azure ...

APIs, files). Leverage the AWS environment, including S3, IAM, and various data services. Prepare data for Data Science teams and integrate AI/ML models into production. Ensure data quality, security, and governance. Provide input on data architecture. Qualifications 5+ years of experience in data engineering, including significant experience … Strong knowledge of data and cloud services including S3, IAM, Glue, and Lambda. Languages: Advanced SQL and Python for data manipulation, automation, and ML integration. Data Engineering: Proven experience in ETL/ELT pipeline design. AI/ML Integration: Ability to prepare data for model training and deploy AI models ...