1 to 25 of 54 Remote/Hybrid Contract Machine Learning Jobs

Role : Machine Learning Infrastructure Developer Location: Cambridge, UK (Hybrid ) Duration: 12 Months Responsibilities: Create robust, flexible, and scalable machine learning tooling and infrastructure that supports research scientists in leveraging large-scale internal infrastructure (e.g., source control, distributed compute clusters, data storage). Work collaboratively as part … signal processing experience . Experience collaborating closely with research users or internal customers to deliver robust, stable, and scalable tooling. Experience writing scalable ML pipelines or tooling used by research teams. Familiarity with Linux or Windows shell scripting. ...

Data Annotator Analyst – AI/Machine Learning – Expedia Group Location: London (hybrid working) Duration: End of 2026 Pay: £223.18/day About the Role We are looking for a Data Annotator/Data Analyst to support the development and evaluation of AI and machine learning solutions. … consistent, and accurate annotations following defined guidelines Analyze annotated data to identify patterns, issues, and opportunities for improvement Work closely with data scientists and ML engineers to refine annotation strategies Use annotation tools (e.g., Label Studio or similar) to manage and review datasets Perform basic data processing and validation using ...

Intelligence/Machine Learning applied to cyber security . This is a research-led role , focused on the security of AI/ML systems , exploring emerging threats, developing novel approaches, and shaping future cyber capability. You will work in an environment where problems are genuinely complex and often … have no off-the-shelf solutions . What You'll Be Doing Conducting hands-on AI/ML research in cyber security, with particular focus on the security of AI/ML systems Designing and prototyping innovative solutions to emerging cyber threats Translating research into practical outputs , including prototypes, reports ...

operational environments. The work is practical, fast-moving and delivery-focused, with models moving into production rather than remaining in research. Ideal for an ML engineer who enjoys solving messy, real-world problems and driving measurable performance improvements. Responsibilities Design, train and optimise computer vision models for vehicle damage detection … computer vision Hands-on experience training and deploying object detection or segmentation models such as YOLO or similar architectures Proficiency in Python and common ML and computer vision libraries Experience working with large image datasets and noisy real-world data Ability to translate operational or business problems into measurable ML ...

optimising, and deploying AI solutions in a fast-moving environment. You’ll work closely with product, data, and engineering teams to design and implement machine learning models, contribute to production-ready pipelines, and help scale AI capabilities across the business. Key Responsibilities: Design, build, and deploy machine … quality, testing, and scalability Required Experience: Proven experience as an AI Engineer or Machine Learning Engineer Advanced Python skills with experience in ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn) Strong understanding of machine learning algorithms and applied AI Experience deploying models into production environments Comfortable working ...

Inside IR35 A global life sciences organisation is seeking a Senior Data Engineer to join a highly technical data platform team working on ML-adjacent initiatives. The environment is cloud-native and highly data-intensive, with a strong focus on unstructured data and scalable pipelines. This is a data engineering … role rather than an ML Engineer or Data Scientist position. The successful contractor will be comfortable operating close to machine learning workflows, particularly working with PyTorch in a cloud environment, but the core responsibility remains data engineering at scale. The RoleYou will be responsible for designing, building ...

working across the full lifecycle from data exploration through to model development validation plus deployment support. Responsibilities for the Data Scientist: Develop statistical models machine learning solutions analytical frameworks to address complex business problems Explore large structured semi-structured datasets to identify patterns trends predictive signals Build test … Data Scientist: Strong experience in data science using Python with libraries such as Pandas NumPy scikit-learn or similar Solid grounding in statistics probability machine learning techniques Proven experience working within cloud environments such as AWS Azure or GCP Experience working with SQL large analytical datasets Ability ...

Details Role/Job Title: AI/ML Architect Work Location: London Mode of Working: Hybrid Office Attendance (Hybrid): 2 days from office Number of Positions: 4 The Role An AI/ML Developer is responsible for designing, building, and deploying machine learning models and AI solutions that … clean, and preprocess large datasets for training and validation. Implement feature engineering and data augmentation techniques. Integration & Deployment Develop APIs or services to integrate ML models into production systems. Work with MLOps tools for model deployment, versioning, and monitoring. Performance Optimization Evaluate models using metrics like accuracy, precision, recall ...

contract basis - Hybrid working - London based The AI Engineer will join a cross-functional data team to design, develop, and deploy AI/ML models that tackle real business problems - from prediction and automation to customer personalisation and decision intelligence. You'll play a hands-on role in taking models … versioning, and monitoring Contribute to documentation, knowledge sharing, and process improvements Profile The AI Engineer will have a proven commercial experience delivering AI/ML projects end-to-end in production environments Strong Python skills with hands-on use of ML libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face ...

Spark, and Delta Lake Build and optimize ETL/ELT workflows for batch and streaming data Develop data models to support analytics, reporting, and machine learning use cases Ensure data quality, reliability, and performance across … data platforms Integrate data from multiple sources including APIs, databases, and cloud storage Collaborate with data scientists and analysts to enable advanced analytics and ML workloads Implement monitoring, logging, and cost-optimization best practices Follow data governance, security, and compliance standards Document data pipelines, architectures, and best practices Required Qualifications ...

satisfaction from day one. Experience in building reusable AI components and frameworks for enterprise-scale deployments.Your CV must evidence strong proficiency in Python and ML frameworks (TensorFlow, PyTorch). You will have strong statistical and analytical skills. You will be experienced in a wide range of Data Science techniques (e.g. … ML, Optimisation, Simulation, GenAI, etc.). You will have demonstrated an ability to take models from design through to production deployment, including performance optimisation, monitoring, and integration into business workflows beyond proof-of-concept or prototype stages. You will have significant experience in similar operational research roles, with a proven ...

vector search technology. Collaborate with cross-functional teams to integrate AI models into products. Stay updated with the latest advancements in AI and machine learning technologies. Conduct research to improve existing AI systems and develop new approaches. Knowledge of NLP, computer vision, or reinforcement learning. Experience deploying … models in production environments. Your Profile Essential Skills/Knowledge/Experience Proven experience in AI, machine learning, or deep learning. Proficiency in programming languages such as Python, R, or Java. Experience with AI frameworks like TensorFlow, PyTorch, or Keras. Experience with large language models (GPT, BERT, etc. ...

Intelligence/Machine Learning, or Maths/Computer Science with AI modules. Recent PhD or Masters relevant to "Cyber Security of AI ML". Experience: Deep AI/ML algorithm and application knowledge (ideally Cyber aspects) Experience of research, innovation and/or solution development. Research Skills: Excellent … report writing and presentation skills. Excellent spoken and written English. Technical skills: Technical specialist in AI/ML/Data Science techniques. Software Development: Strong Python skills. Academic research background PHD/Masters within the last 5-10 years Deep AI/ML algorithm and application knowledge (ideally Cyber aspects ...

test: Prompt-level guardrails. Safety classifiers Behaviour-shaping or reward-modelling components. LLM and multimodal fine-tunes Adversarial robustness defences Use Python and modern ML frameworks (e.g., PyTorch, TensorFlow, JAX, HuggingFace). Contribute to creation of synthetic datasets, adversarial evaluation corpora, and scenario-based test sets. Help transition research outputs … platform direction. Key Skills and Experience Strong Python programming skills and foundations in machine learning, LLMs, or multimodal AI. Understanding of ML concepts such as training, fine-tuning, optimisation, evaluation, and model drift. Experience building or adapting ML models (open-source or proprietary). Ability to design structured ...

data governance frameworks Strong understanding of data security, access controls, and compliance requirements Excellent problem-solving, communication, and documentation skills Familiarity with AI/ML data pipelines and analytics platforms Preferred Qualifications Experience with cloud data platforms (AWS, Azure, GCP) Experience with big data technologies (Hadoop, Spark, Kafka) Familiarity with ...

LLMs, and enterprise AI technologies. Your Profile Essential skills/knowledge/experience 5 8 years of experience in software engineering or AI/ML development, with at least 4+ years working with Azure AI services. Strong hands-on experience with Azure AI Doc Intelligence, including document extraction, form recognizers ...

processes (such as DBT), SQL, NoSQL databases is added advantage. Experience with data visualization tools and DevOps principles/tools is advantageous. Familiarity with machine learning and AI concepts, particularly in how they integrate into data architectures. Design and Lifecycle Management: Proven background in designing modern, scalable ...

senior IC role focused on building and optimising distributed data pipelines that power pricing, forecasting and billing calculations at scale. - This is not an ML/Data Science/GenAI role What youll be doing Design, build and deploy algorithms/data models supporting pricing, forecasting and optimisation use cases ...

Streaming) Infrastructure-as-code experience (Bicep, Terraform) CI/CD tooling (Azure DevOps, GitHub Actions) Familiarity with data governance and cataloging tools Experience supporting ML or advanced analytics workloads What We're Looking For Strong problem-solving and analytical mindset Ability to work independently and as part of a cross ...

Azure AI Foundry, Azure OpenAI, Azure AI Document Intelligence design and deploy. You should have hands-on experience in Azure Data Factory, Azure ML Service, Azure Data bricks, Azure Key Vault, Azure BLOB Storage Account, Azure Log Analytics, Synapse Analytics, Azure DevOps. You will define the reference architectures and guardrails …/knowledge/experience 15+ years overall in software/solution architecture with 7+ years in cloud (Azure) and 5+ years in AI/ML or Azure AI solutioning. Proven experience leading production grade solutions using Azure OpenAI, Azure AI Foundry, Azure AI Document Intelligence, Azure Data Factory, Azure ML ...

with Databricks , Kafka , or Kinesis for real-time data streaming Knowledge of containerisation (Docker, ECS) and modern orchestration tools such as Airflow Familiarity with machine learning model deployment pipelines or data lakehouse architectures Data Engineer, AWS Data Engineer ...

governance and performance requirements Contribute to best practice around AI engineering, MLOps and deployment patterns Required Experience Proven experience as an AI Engineer/ML Engineer delivering AI into production Strong Python development skills Hands-on experience with LLMs (commercial and/or open-source) Experience building APIs and services ...

skilled Data Engineer to design, build, and optimize enterprise-scale data pipelines and cloud platforms. You will translate business and AI/ML requirements into robust, scalable solutions while collaborating across multi-disciplinary teams and external vendors. As a key member of the data architecture you will: Build and orchestrate … with cloud platforms (Snowflake, AWS fundamentals). Solid understanding of data architecture, warehousing, and modeling. Programming expertise: Python, Spark, SQL, API integration. Knowledge of ML/AI frameworks, MLOps, and advanced analytics concepts. Experience with CI/CD, data testing frameworks, and versioning strategies. Ability to work effectively in multi ...

work on practical, production software that supports engineering teams day to day. While some solutions use data-driven or automation techniques (including AI/ML), the role is fundamentally about strong software engineering , sound judgement, and reliability. What You'll Be Doing Hands-on software engineering Design, build, test … Experience in engineering, industrial or regulated environments Exposure to cloud platforms (e.g. AWS) Experience with data-heavy systems, automation or analytics Some familiarity with machine learning or optimisation concepts (not essential) Why Join A 12-month contract with strong extension potential Competitive £54/hr umbrella rate (inside ...

Stack: Strong Python , SQL , and Java . AI Specialist: Hands-on experience with LLMs and prompt engineering. Academic: MSc/PhD in AI/ML (Safety or Agentic systems focus preferred). This is an urgent vacancy with a deadline where the hiring manager is shortlisting for an interview immediately. ...