18 of 18 Remote Machine Learning Jobs in Slough

Scientist and help make a difference for small businesses! We contribute to innovative machine learning models for Pricing + Bundling and Generative AI projects. Collaborate with ML engineers to develop ML pipelines and ensure the quality and reliability of our ML solutions. What you'll get to do... Develop and implement sophisticated algorithms for Pricing and AI … projects using PyTorch. Craft and refine ML models to improve their performance, scalability, and adaptability. Analyze and interpret complicated data sets to advise model development and ensure accuracy and efficiency. Stay abreast of the latest developments in ML and artificial intelligence, integrating new methodologies and techniques as appropriate. Collaborate across multiple teams to integrate ML solutions within broader product and … platform initiatives. Contribute to the development of standardized processes for model evaluation, validation, and deployment to production environments. Drive the exploration and adoption of brand new ML technologies to maintain our competitive edge in the industry. Your experience should include... 4+ years of overall experience and 2+ years of experience in machine learning engineering or related roles. 3+ More ❯

About the Opportunity: We are seeking an ambitious and intellectually curious Junior Data Scientist to join a fast-growing, forward-thinking team working at the forefront of data science, machine learning, and applied AI. This is an excellent opportunity for a recent Master’s graduate eager to apply their academic expertise to solving real-world challenges—whether it … s predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What You’ll Be Doing: Designing and building machine learning models to solve real-world … B testing Presenting findings clearly to both technical and non-technical stakeholders Collaborating across data science, engineering, and product teams to build scalable solutions Staying current with advancements in machine learning and AI, and contributing new ideas to internal R&D discussions What We’re Looking For: A recently completed Master’s degree from a Russell Group university More ❯

processing. Responsibilities Develop, train, and optimise computer vision models for real world applications. Work with large datasets including images and video, ensuring data preprocessing, augmentation, and pipeline optimisation. Deploy ML models into production, ensuring scalability, efficiency, and reliability. Collaborate closely with data scientists, software engineers, and product teams to translate business needs into technical solutions. Stay up to date with … in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or … with transformer-based vision models (ViT, CLIP, SAM). Familiarity with real-time inference and optimisation (ONNX, TensorRT). Previous work on video analytics, 3D vision, or multi-modal ML projects. More ❯

decisions and solution governance. Write 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 control, performance optimisation, and maintainability. … of RESTful API design, authentication/authorization standards, and API lifecycle best practices; familiarity with Microsoft Graph API is a plus. Experience & Knowledge Requirements Good knowledge of generative AI, machine learning … deep learning, natural language 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, MLflow, LangChain, LangGraph. Proven experience More ❯

a strong foundation in data science who is looking to make a meaningful impact in a high-performance, fast-paced environment. Key responsibilities Design, build, and maintain statistical or machine learning models to support sports forecasting and pricing across various markets. Extract actionable insights from large-scale sports datasets using sound mathematical and statistical principles. Translate modelling requirements … Experience working with Python or R in a production or research setting. Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. Ability to explain model behaviour through visualisations … contribute to cross-functional discussions. Proven problem-solving and time management skills. Desirable: Familiarity with cloud services (e.g. AWS S3, Athena, Lambda). Basic understanding of data engineering or ML pipelines. Knowledge of distributed systems (e.g. Kafka). Interest in American sports or the betting industry. Some exposure to .NET-based systems or application integration. Follow our company page, OTA More ❯

Job Title: Contract Deep Learning Engineer Location: London (Hybrid or On-site) Contract Type: 6–12 months (with potential extension) About the Role: We are seeking a highly skilled Deep Learning Engineer to join our team on a contract basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world … computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define model requirements and deployment strategies. Optimize model performance and scalability for production environments. Conduct experiments, evaluate model performance, and iterate based on results. Maintain … to knowledge sharing across the team. Stay up-to-date with the latest research and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience More ❯

building the world’s first brain foundation models — large-scale AI systems designed to deeply understand, protect, and enhance the human brain. By generating our own data, developing novel machine learning approaches, and working closely with world-leading neuroscientists, the company aims to accelerate discoveries that transform how neurological diseases are treated and prevented. This is a rare … real-world insights from raw biological data. Key Responsibilities Design and implement distributed data pipelines for multi-omic, neuroscience, and clinical datasets Build a unified feature store to serve ML training and downstream biological analysis Develop scalable storage, ingestion, and validation systems with a focus on robustness, observability, and versioning Collaborate with ML researchers and biologists to translate raw data … Flyte/Temporal) Hands-on cloud engineering experience (AWS, GCP, or Azure) Strong software engineering fundamentals, with a track record of writing maintainable, testable, and extensible code Familiarity with ML infrastructure and prior experience supporting ML teams in production environments Bioinformatics or biological data exposure (preferred, not required) — willingness to learn is essential Excellent communication skills and ability to collaborate More ❯

Technical Skills (desirable): Microsoft Azure Data Services (e.g., Azure Data Factory, Synapse, Databricks, Fabric) Data warehousing and lakehouse design ETL/ELT pipelines SQL, Python for data manipulation and machine learning Big Data frameworks (e.g., Hadoop, Spark) Data visualisation (e.g., Power BI) Understanding of statistical analysis and predictive modelling Experience: 5+ years working with Microsoft data platforms 5+ More ❯

in partnership with approved vendors—to align on business needs, define use cases and develop implementation plans as part of overall product roadmap. Collaborate with team-members (software engineer, ML engineers, data engineers, product owners, etc.) in design reviews and critical feedback sessions to continuously improve product delivery Partner with and influence stakeholders across the insights & analytics space and in More ❯

and scaling BI teams. Experience delivering BI strategies and aligning analytics with business KPIs. Background in Azure data platforms. Desirable: Python for automation and analytics. Exposure to AI/ML-driven BI (e.g. natural language querying, automated insights). Experience with CI/CD for BI solutions and version control (Git). Interview Process: Initial screening call. Face-to-face More ❯

Month Rolling Contract | Long-Term Engagement Location: London Skills: Python/Azure/Databricks/Snowflake The Role: Design and build powerful data pipelines that fuel real-time decisions, machine learning, and next-gen analytics at scale. Transform raw data into trusted, usable assets - the foundation for everything from executive dashboards to product innovation. Own the data flow More ❯

Tools (e.g. Adobe Analytics, Amplitude, Mixpanel). Ability to set up behavioural tracking measurement plans (e.g. designing events schemas). Strong analytical skills, including A/B Testing, foundational Machine Learning concepts, Data Visualisation and Storytelling. Good communication and stakeholder management skills, experience working in cross functional/embedded analytics teams. Good strategic and business thinking, allowing to More ❯

Project Lead (Contract - Outside IR35) 📍 UK (Remote/Hybrid) | 💰 £480 £520/day | 🚀 Start ASAP We are working with a creative, tech-forward agency delivering real-world AI/ML solutions across industries. With demand surging, they are hiring a Senior AI Project Lead to drive delivery on high-impact LLM and automation projects. 🔹 ~70% leadership/~30% technical 🔹 Lead More ❯

with engineering teams on complex technical products. A customer-driven mindset with a track record of using deep research and data to drive product decisions. Experience with AI/ML products that leverage advanced technology to deliver customer value is a plus. Why This Role Matters Direct Customer Impact: You will drive products that meaningfully improve outcomes for enterprise customers More ❯

a Data Privacy Lawyer for their UK operation. 12 month fixed term contract Hybrid working arrangement (with flex) Extremely varied role working across cutting edge tech/AI/machine learning etc. Ideally looking for an experienced Data Privacy Lawyer (UK or EU qualified) with an interest in the retail/consumer sector. Great opportunity to work for More ❯

multiple workstreams cross-functionally. Experienced in leading EDAs, defining client use cases, and collaborating with data analysts and scientists. Comfortable engaging with emerging technologies such as APIs, data science, machine learning, and AI. Collaborative team player with a proactive and growth-oriented mindset. Benefits Hybrid working environment Comprehensive onboarding and training Internal and global mobility opportunities Competitive healthcare More ❯

agents into ticketing, voice, and analytics stacks (APIs, webhooks, real‐time streams). Partner with PMs/CX to evolve taxonomies, schemas, and guardrails; translate business problems into shipped ML features. 10% Align & showcase Gather requirements from CX and product leads, demo new capabilities to execs & customers, and document impact with precision/recall, alert quality, latency, and cost metrics. … no silos, and carry work from prototype to production. 🛠️ AI‐native dev tools are your daily drivers: Cursor, v0, Claude Code (or similar). 7–10 years building production ML/back‐end systems; 2+ years leading while coding. Expert Python ; strong back‐end chops (e.g., FastAPI, gRPC, Postgres, pub/sub/streams). Agents & RAG: Fluency with at More ❯

powered workflows. Architect full-stack solutions using RAG, fine-tuning, and scalable inference endpoints. Support pre-sales efforts, workshops, and proof-of-concepts alongside go-to-market teams. AI & ML Engineering Implement and optimise AI/ML models using frameworks like PyTorch, HuggingFace, LangChain, and NVIDIA Triton. Fine-tune foundation models for domain-specific use cases. Deploy and maintain inference … sales and solution support. Maintain high client satisfaction scores post-deployment. Produce thought leadership (blogs, talks, case studies) on real-world AI implementation. Required Qualifications Background in AI/ML engineering, applied AI, or technical solutions delivery. Strong experience with: Retrieval-Augmented Generation (e.g., LangChain, LlamaIndex, vector databases). LLM fine-tuning techniques (LoRA, PEFT, instruction tuning). Deploying models … cloud AI platforms). Awareness of UK AI compliance and data sovereignty regulations (e.g., ISO 27001, SOC 2). Experience optimising GPU workloads. Contributions to open-source AI/ML projects or toolkits. Compensation & Benefits Competitive salary Potential equity or performance-based incentives Learning and development budget Hybrid work flexibility with occasional client or team site visits If you More ❯