ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . Hands-on experience with MLOps tools (MLflow, SageMaker, Kubeflow, etc.) and version control systems. Strong knowledge of APIs, microservices architecture, and CI/CD pipelines. Proven experience in leading teams, managing stakeholders, and delivering end-to-end More ❯
XGBoost, LightGBM, or similar Strong SQL skills and experience with data warehousing solutions (Snowflake, BigQuery, Redshift) Experience with cloud platforms (AWS, Azure, GCP) and their ML and AI services (SageMaker, Azure ML, Vertex AI) Knowledge of MLOps tools including Docker, MLflow, Kubeflow, or similar platforms Experience with version control (Git) and collaborative development practices Excellent analytical thinking and problem More ❯
Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow, Spark) Proficient in both SQL (PostgreSQL, MySQL) and NoSQL (Elasticsearch, MongoDB More ❯
Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow, Spark) Proficient in both SQL (PostgreSQL, MySQL) and NoSQL (Elasticsearch, MongoDB More ❯
for data/AI), SQL Cloud & DevOps: AWS/Azure/GCP services, CI/CD pipelines, Docker/Kubernetes AI/ML Tooling: Familiarity with cloud AI services (SageMaker, Vertex AI, Azure AI) and ML lifecycle management Data: Relational & NoSQL databases, data modelling, ETL/ELT, BI tools Strategic thinker with commercial acumen; can link technology to bottom More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Willis Global
for data/AI), SQL Cloud & DevOps: AWS/Azure/GCP services, CI/CD pipelines, Docker/Kubernetes AI/ML Tooling: Familiarity with cloud AI services (SageMaker, Vertex AI, Azure AI) and ML lifecycle management Data: Relational & NoSQL databases, data modelling, ETL/ELT, BI tools Strategic thinker with commercial acumen; can link technology to bottom More ❯
to support decisions across multiple business areas, including marketing, sales, claims, retention, customer behavior, fraud detection, and customer servicing. Deploy machine learning models into production using AWS services, including SageMaker, S3, Feature Store, ensuring scalable, reliable, and monitored solutions that directly support key business processes. Collaborate with product management and engineering teams to integrate data-driven insights and deploy More ❯
AI assistants and agentic tools to maximise impact. Bonus points if you’ve played with: LangGraph, AutoGen, or other agentic AI frameworks LoRA fine-tuning, RLHF, or vLLM AWS (SageMaker, EKS), Docker, or speech-to-text systems 🌟 What You Get: 100% remote role (UK or Spain) Work on real-world LLM deployments in an agile, experimental environment More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Omnis Partners
AI assistants and agentic tools to maximise impact. Bonus points if you’ve played with: LangGraph, AutoGen, or other agentic AI frameworks LoRA fine-tuning, RLHF, or vLLM AWS (SageMaker, EKS), Docker, or speech-to-text systems 🌟 What You Get: 100% remote role (UK or Spain) Work on real-world LLM deployments in an agile, experimental environment More ❯
independently Excellent communication skills across technical and non-technical stakeholders Experience designing systems in modern cloud environments (e.g. AWS, GCP) Technologies and Tools Python ML and MLOps tooling (e.g. SageMaker, Databricks, TFServing, MLflow) Common ML libraries (e.g. scikit-learn, PyTorch, TensorFlow) Spark and Databricks AWS services (e.g. IAM, S3, Redis, ECS) Shell scripting and related developer tooling CI/ More ❯
Milton Keynes, Buckinghamshire, South East, United Kingdom Hybrid / WFH Options
LA International Computer Consultants Ltd
and development to succeed. A progressive organisation where you can really make a difference. We a great opportunity for a Data Scientist. You will have solid experience of Bedrock, Sagemaker, Python and Pandas. Key Responsibilities: * Working experience LLMs under Bedrock and Sagemaker both Amazon * Python with APIs to ChatGPT * Strong coding skills using libraries like pandas, NumPy … Experience: AWS Data Science Environment: Hands-on experience with Sage Maker, Lambda, Step Functions, S3, Athena. Model deployment and pipeline orchestration in AWS. OCR Use-Case Development: Proficiency with Amazon Tex-tract, Tesseract, and LLM-based OCR. Building document parsing pipelines, validations, and rule Python Proficiency: Strong coding skills using libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging … actionable insights. Stakeholder Collaboration: Effective communication with technical and non-technical stakeholders. Experience in cross-functional team. Data Engineering Basics: Familiarity with SQL and big data processing tools (e.g., Amazon Athena). Model Evaluation & Experimentation: A/B testing, statistical analysis, and performance metrics. Security & Compliance Awareness: Understanding of data privacy, PII handling, and compliance standards (e.g., GDPR). More ❯
of AI frameworks (TensorFlow, PyTorch, Keras) Experience with NLP and computer vision models Strong understanding of machine learning algorithms and statistical modeling Experience with cloud-based AI platforms (AWS SageMaker, Google Cloud AI Platform) Excellent problem-solving and communication skills Qualifications Master's degree in Computer Science, Artificial Intelligence, or related field Certified AI Engineer or related certification (optional More ❯
into DV and undertake occasional overseas assignments • Strong team player with a proactive mindset, eager to shape new delivery teams Desirable Skills • Exposure to cloud ML platforms (e.g., AWS Sagemaker, Azure ML) • Experience deploying data/API services and microservice architectures • Previous consulting or defence/national security sector experience • Familiarity with Ansible or similar configuration management tooling Package More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Robert Half
TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker, Vertex AI) Comfortable working independently and delivering high-quality work to tight timelines Experience working in fast-paced environments or scale-up settings Company Market leading financial services (fintech More ❯
and optimize AWS-based data infrastructure, including S3 and Lambda, as well as Snowflake. Implement best practices for cost-efficient, secure, and scalable data processing. Enable and optimize AWS SageMaker environments for ML teams. Collaborate with ML, Data Science, and Reporting teams to ensure seamless data accessibility. Implement data pipeline monitoring, alerting, and logging to detect failures and performance More ❯
Leeds, Yorkshire, United Kingdom Hybrid / WFH Options
William Hill PLC
solutions in complex enterprise environments Experience in all architecture domains:- application, data, cloud ( AWS) and technology with expertise with AI, Gen Ai and ML frameworks (e.g., TensorFlow, PyTorch, AWS Sagemaker, AWS Bedrock, OpenAI). Strong experience of AI services and AI lifecycle and model training Proficiency in backend and frontend technologies such as .NET Core, Node.js, and React; familiarity More ❯
direction across multiple teams. • Extensive experience in large scale machine learning, including building, deploying, scaling and securing ML infrastructure in cloud-native environments. • Strong experience with AWS services including SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS, DynamoDB, Kafka, CloudFormation and associated technologies such as Python • Proven ability to drive cross functional technical initiatives and deliver results More ❯
communicate technical ideas through writing, visualisations, or presentations Strong organisational skills with experience in balancing multiple projects Familiarity with Posit Connect, workflow orchestration tools (e.g., Airflow), AWS services (e.g., SageMaker, Redshift), or distributed computing tools (e.g., Spark, Kafka) Experience in a media or newsroom environment Agile team experience Advanced degree in Maths, Statistics, or a related field What's More ❯
Terraform for infrastructure management Grafana, Elasticsearch, Kibana & New Relic for metrics, logs and monitoring In the company we also use: VueJS, MySQL, Spring Boot, Apache Camel, AWS Redshift, AWS SageMaker, Pentaho, Balena, Serverless functions Winnow has adopted a hybrid working model where employees come to the office two days a week and can choose to work from home or More ❯
Lancaster, Lancashire, United Kingdom Hybrid / WFH Options
Galaxy Systems
modern frameworks. Build and optimize RAG pipelines using models like GPT, Claude, or other LLMs integrated with document retrieval systems. Develop production-ready ML applications in cloud environments (AWS, SageMaker, Databricks, etc.). Leverage GPU-based computing resources and CUDA/Nvidia for performance optimization in training and inference. Collaborate with data engineers, software developers, and product teams to … experience with PyTorch, TensorFlow, Scikit-learn, and transformer-based models. Practical knowledge of LLM integration (e.g., GPT, Claude) and RAG architecture. Experience with ML lifecycle management tools like AWS SageMaker, MLflow, or Databricks. Working knowledge of CUDA, Nvidia GPUs, and distributed training. Experience with AWS services (S3, Lambda, EC2, SageMaker, Bedrock, etc.). Desired: Experience deploying models as More ❯
