1 to 25 of 27 Permanent Amazon SageMaker Jobs in London

large language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data ...

models in Python Proficiency with ML frameworks such as scikit-learn, XGBoost, PyTorch or TensorFlow Strong experience delivering ML solutions using AWS services (e.g. SageMaker, Lambda, S3) Expertise in experiment design, including hypothesis formulation, A/B testing and statistical evaluation Proven experience moving models from experimentation into production ...

Awareness of ethical, privacy, security and policy considerations in applied AI Desirable Experience Hands-on experience with AWS services such as Lambda, ECS, S3, SageMaker or Bedrock Knowledge of ML engineering and MLOps practices (e.g. Docker, MLflow) Experience working in government, defence or other highly regulated environments Proven application ...

data science roles (senior level). Hands-on experience with Python ML frameworks (scikit-learn, PyTorch, TensorFlow, XGBoost). Experience with AWS ML services (SageMaker, Lambda, S3) and MLOps/LLMOps tooling (MLflow, Weights & Biases, DVC). Proven track record transitioning models from experimentation to production with governance ...

experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow. Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments. Strong experiment design skills: hypothesis formulation, A/B testing, and statistical evaluation. Proven track record transitioning models from ...

Experience In Some Of These, But If Not Well Help You With Them Good knowledge of AWS cloud services (e.g. Lambda, ECS, Bedrock, S3, Sagemaker) ML Engineering and MLOps knowledge (e.g. Docker, ML flow) Experience working with government or other carefully regulated industries Track record of applying LLMs ...

APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools (e.g., MLflow, Azure ML, Databricks, SageMaker or Vertex) plus observability practices. Familiarity with higher education processes and integrations across SIS, LMS, CRM, and ERP environments. Knowledge of data privacy, accessibility ...

engineers What We're Looking For: Proficiency in Python and ML frameworks (scikit-learn, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda) Familiarity with containerisation (Docker) and orchestration (Kubernetes/ECS) Knowledge of LLMOps and GenAI tools (LangChain, LangSmith) Understanding of feature engineering and vector databases ...

experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology, and statistical evaluation Proven track record transitioning models ...

technical concepts to diverse audiences. Eligible for DV security clearance; sponsorship cannot be provided. Desirable: Knowledge of AWS services (e.g., Lambda, ECS, Bedrock, S3, SageMaker). Experience with ML engineering and MLOps (e.g., Docker, MLflow). Experience in regulated industries or government-related projects. Applying LLMs or advanced ...

inference Advanced Python skills (NumPy, pandas, scikit-learn, PyTorch or TensorFlow) Experience building, deploying and optimising ML models in production Strong AWS experience (e.g. SageMaker, Lambda or similar services) Expert SQL skills and experience working with large, complex datasets Solid data engineering fundamentals, including pipelines and APIs Comfortable with ...

have: Strong Python ML experience (e.g. scikit-learn, XGBoost, PyTorch, or TensorFlow) Production experience with AWS ML services (e.g. SageMaker, Lambda, S3) Proven ability to move models from experimentation into live systems Experience with MLOps tools (MLflow, Weights & Biases, DVC, or similar) Hands-on exposure to LLM/GenAI ...

experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology, and statistical evaluation Proven track record transitioning models ...

deploying LLMs at scale Familiarity with cloud infrastructure and distributed computing environments Exposure to modern ML tooling such as Modal, Weights & Biases, or Amazon SageMaker Knowledge of fine-tuning techniques including LoRA, QLoRA, or other parameter-efficient frameworks Role Overview The successful candidate will be responsible for designing ...

scikit-learn, PyTorch, transformers) Experience deploying models and working with cloud platforms (AWS preferred) Ability to communicate complex technical concepts clearly Desirable AWS services (SageMaker, ECS, Lambda, S3, Bedrock) MLOps/ML engineering experience (Docker, MLflow) Experience in government or regulated environments Practical experience applying LLMs Security Clearance UKIC ...

serverless GenAI workflows for scalable, secure deployment. ML/LLM Engineering & LLMOps Work across AI/ML platforms such as Azure ML, AWS SageMaker, Vertex AI, Databricks, Modal, and Fly.io. Deploy and manage vector databases and embedding stores, including Pinecone, Weaviate, Milvus, FAISS, ChromaDB, and pgVector. Implement LLMOps/ ...

PyTorch Experience with containerization tools like Docker and orchestration tools like Airflow or Astronomer Familiarity with cloud platforms (AWS, Azure) and ML services (e.g., SageMaker, Vertex AI) Experience with CI/CD pipelines and automation tools such as GitHub Actions Understanding of monitoring and logging tools (e.g., NewRelic, Grafana ...

constraints, monitoring and prompt versioning Strong Python skills and experience with PyTorch, TensorFlow or Keras Exposure to MLOps practices and hands-on experience with Sagemaker and/or Vertex AI Bachelor's degree in a technical field such as computer science or years of equivalent experience Comfortable working autonomously ...

constraints, monitoring and prompt versioning Strong Python skills and experience with PyTorch, TensorFlow or Keras Exposure to MLOps practices and hands-on experience with Sagemaker and/or Vertex AI Bachelor's degree in a technical field such as computer science or years of equivalent experience Comfortable working autonomously ...

detail, and ability to work independently and collaboratively Highly desirable AWS certifications (e.g., DevOps Engineer, Solutions Architect) Experience with AWS generative AI services (Bedrock, SageMaker) Open-source contributions demonstrating engineering best practices Benefits Work on cutting-edge generative AI projects Join a talented, innovative team Competitive salary and benefits ...

technical stakeholders Mentor junior team members Skillset: Strong Python and ML libraries (scikit-learn, PyTorch, pandas, NumPy) Experience with AWS cloud services (SageMaker, Lambda, S3) Familiarity with MLOps tools (MLflow, Weights & Biases) Knowledge of NLP, computer vision, or time-series analysis Ability to design experiments and apply statistical validation ...

Have: • Built agentic workflows/LLM tool-use. • Experience with MLFlow, Arize, LangFuse, or other MLOps tools. • Experience with deploying ML models on SageMaker, KServe, or similar. Why Plexe? • Hard problems: we're automating the entire ML/AI lifecycle from data engineering to insights. • High ownership: first ...

LLMs (Large Language Models), generative models, and related frameworks (e.g., LangChain, TensorFlow, etc.) Possess knowledge of cloud-based AI/ML services like AWS SageMaker, Azure Machine Learning, Google AI Platform, Databricks GenAI/BI, Snowflake GenAI, and their relevant services for building and deploying GenAI workloads. Knowledge ...

CodeBuild, Jenkins, and Ansible; manage VPCs, RDS, and Elastic Beanstalk for Flex workloads. Enhance Flex with AI/ML integrations (e.g., AWS Lex, SageMaker) and performance tuning for global scale. Lead troubleshooting, security audits (IAM, GuardDuty), and cost optimization in dynamic environments. Requirements: 5+ years AWS DevOps experience (hands ...

/Knowledge Graph expertise - deep knowledge with Knowledge Graphs and vector databases Strong technical fluency - TypeScript/React, Langgraph/Langchain, neo4j, Docker, AWS (SageMaker, Bedrock, Hugging face), to name a few Benefits include: Flexibility - the team works fully remotely, albeit with frequent meetups to share ideas Stock options ...