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 ❯
and API design Hands on experience in using one of 3 major cloud technologies (AWS, Azure or GCP) in a production environment, as well as ML platforms (e.g., AWS Sagemaker, Azure Machine Learning studio) Be a lifelong learner and can demonstrate a drive to always be learning and developing your skillsets and develop the skillsets of others around you 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 ❯
classification, decision trees, support vector machines, and neural networks (deep learning experience strongly preferred) Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g., AWS Bedrock, S3, SageMaker; Azure AI Search, OpenAI, blob storage, etc. Bachelors degree (masters or higher strongly preferred) in machine learning, computer science, data science, applied mathematics or related technical field What Would More ❯
delivery Proven track record deploying ML systems in production at scale (batch and/or real-time) Strong technical background in Python and ML engineering tooling (e.g. MLflow, Airflow, SageMaker, Vertex AI, Databricks) Understanding of infrastructure-as-code and CI/CD for ML systems (e.g. Terraform, GitHub Actions, ArgoCD) Ability to lead delivery in agile environmentsbalancing scope, prioritisation 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 ❯
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 ❯
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 ❯
Whetstone, Greater London, UK Hybrid / WFH Options
Compare the Market
wed like to see from you: Extensive experience designing and deploying ML systems in production Deep technical expertise in Python and modern ML tooling (e.g. MLflow, TFX, Airflow, Kubeflow, SageMaker, Vertex AI) Experience with infrastructure-as-code and CI/CD practices for ML (e.g. Terraform, GitHub Actions, ArgoCD) Proven ability to build reusable tooling, scalable services, and resilient More ❯
wed like to see from you: Extensive experience designing and deploying ML systems in production Deep technical expertise in Python and modern ML tooling (e.g. MLflow, TFX, Airflow, Kubeflow, SageMaker, Vertex AI) Experience with infrastructure-as-code and CI/CD practices for ML (e.g. Terraform, GitHub Actions, ArgoCD) Proven ability to build reusable tooling, scalable services, and resilient 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 ❯
