101 to 125 of 178 Remote Amazon SageMaker Jobs

culture of curiosity, support and honesty. Nice to have: Knowledge of R or other programming languages Knowledge of current UK AI/ML compliance and regulation. Experience with AWS Sagemaker Experience with Snowflake Experience with Databricks As an inclusive employer, we want to ensure that all candidates feel comfortable and can perform at their best during the interview. You More ❯

culture of curiosity, support and honesty. Nice to have: Knowledge of R or other programming languages Knowledge of current UK AI/ML compliance and regulation. Experience with AWS Sagemaker Experience with Snowflake Experience with Databricks As an inclusive employer, we want to ensure that all candidates feel comfortable and can perform at their best during the interview. You More ❯

culture of curiosity, support and honesty. Nice to have: Knowledge of R or other programming languages Knowledge of current UK AI/ML compliance and regulation. Experience with AWS Sagemaker Experience with Snowflake Experience with Databricks As an inclusive employer, we want to ensure that all candidates feel comfortable and can perform at their best during the interview. You More ❯

Driven Design approaches 1+ years in enterprise technology professional services, in a consulting or other customer-facing delivery role AI-specific tools such as TensorFlow, Google Cloud AI Platform, Amazon SageMaker, etc Working in a number of distinct industries/verticals Success measures Within 3 months: Complete internal training on MongoDB Be connected to the broader AI-focused More ❯

will play a key role in designing and implementing AI-driven solutions, leveraging Large Models (LLMs), Generative AI, Open-Source AI tools, and AWS technologies such as Athena and SageMaker . This position requires strong technical expertise, problem-solving skills, and the ability to work collaboratively within a global AI-focused team. Key Responsibilities Develop and optimise AI and … machine learning models, with a focus on NLP and Generative AI . Design, implement, and deploy scalable AI solutions using AWS services , including Athena, SageMaker, and Lambda. Work with LLMs and Open-Source AI frameworks , ensuring model efficiency and accuracy. Collaborate with cross-functional teams to integrate AI-driven capabilities into business applications. Conduct performance optimisation and fine-tuning … ML frameworks such as TensorFlow, PyTorch, and Hugging Face. Extensive experience in NLP and Generative AI , including working with large-scale models. Proficiency in AWS cloud computing , including Athena, SageMaker, and related AI/ML services. Experience in AI model optimisation, fine-tuning, and deployment in production environments. Strong analytical skills with the ability to solve complex AI-related 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 ❯

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 ❯

just file handling). Understanding and experience of Data Governance frameworks and implementation. Exposure to CI/CD pipelines and source control for reports and analytics. Bonus: Familiarity with SageMaker or similar ML/predictive analytics platforms. We’re looking for someone who: Thinks like a data user, not just a data builder, with a strong sense of how More ❯

performing data science teams. Excellent stakeholder management and communication skills – able to explain complex concepts in accessible language. Proficiency in tools such as Azure ML Studio , Databricks , AWS/SageMaker , Snowflake , and cloud-native platforms. Familiarity with CI/CD tools like Azure DevOps Pipelines or GitHub Actions . Comfortable working in Agile environments and contributing to iterative product More ❯

performing data science teams. Excellent stakeholder management and communication skills – able to explain complex concepts in accessible language. Proficiency in tools such as Azure ML Studio , Databricks , AWS/SageMaker , Snowflake , and cloud-native platforms. Familiarity with CI/CD tools like Azure DevOps Pipelines or GitHub Actions . Comfortable working in Agile environments and contributing to iterative product More ❯

performing data science teams. Excellent stakeholder management and communication skills – able to explain complex concepts in accessible language. Proficiency in tools such as Azure ML Studio , Databricks , AWS/SageMaker , Snowflake , and cloud-native platforms. Familiarity with CI/CD tools like Azure DevOps Pipelines or GitHub Actions . Comfortable working in Agile environments and contributing to iterative product More ❯

PyTorch, scikit-learn, Keras, Natural Language Processing (NLP), Hugging Face Transformers, Pandas, NumPy, Jupyter Notebooks, Matplotlib, Seaborn, Flask (for building APIs), FastAPI, Docker, MLflow, DVC (Data Version Control), AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform, TensorFlow Serving, ONNX (Open Neural Network Exchange) We have several exciting new positions available for Machine Learning Engineers to join a forward … PyTorch, scikit-learn, Keras, Natural Language Processing (NLP), Hugging Face Transformers, Pandas, NumPy, Jupyter Notebooks, Matplotlib, Seaborn, Flask (for building APIs), FastAPI, Docker, MLflow, DVC (Data Version Control), AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform, TensorFlow Serving, ONNX (Open Neural Network Exchange) This is your chance to contribute to an innovative, technically demanding project focused on developing More ❯

with product managers and engineers to explore product innovations arising from emerging technologies and new customer use cases. Technology You'll Use Python, pandas, PyTorch, Databricks, Snowflake, AWS Bedrock, SageMaker, Azure ML, Google Vertex AI Your Role Responsibilities Research and develop expertise in product innovation areas including unstructured data management, AI governance, and protected cross-entity data sharing. Conduct … including libraries like pandas, PyTorch, matplotlib, and Seaborn, with experience in data science and engineering. Experience with cloud service technologies and enterprise tools such as Databricks, Snowflake, AWS Bedrock, SageMaker, Azure ML, and Google Vertex AI. Role Essentials Postgraduate education in Science, Technology, Engineering, or Mathematics. BA/BS or equivalent, or relevant combination of education and experience. Minimum More ❯

Desirable experience: Familiar with Terraform, from a developer perspective. Previous work in financial services, healthcare, or similarly regulated data environments. Experience with LLMs, voice agents, or tools like AWS SageMaker, AWS Bedrock, or ElevenLabs. Exposure to soft real-time systems or distributed system architectures. Knowledge of OAuth, SQS, or running containers in production. More ❯

Desirable experience: Familiar with Terraform, from a developer perspective. Previous work in financial services, healthcare, or similarly regulated data environments. Experience with LLMs, voice agents, or tools like AWS SageMaker, AWS Bedrock, or ElevenLabs. Exposure to soft real-time systems or distributed system architectures. Knowledge of OAuth, SQS, or running containers in production. More ❯

Desirable experience: Familiar with Terraform, from a developer perspective. Previous work in financial services, healthcare, or similarly regulated data environments. Experience with LLMs, voice agents, or tools like AWS SageMaker, AWS Bedrock, or ElevenLabs. Exposure to soft real-time systems or distributed system architectures. Knowledge of OAuth, SQS, or running containers in production. More ❯

Desirable experience: Familiar with Terraform, from a developer perspective. Previous work in financial services, healthcare, or similarly regulated data environments. Experience with LLMs, voice agents, or tools like AWS SageMaker, AWS Bedrock, or ElevenLabs. Exposure to soft real-time systems or distributed system architectures. Knowledge of OAuth, SQS, or running containers in production. More ❯

Docker, Git, cloud networking, and cloud security for services and infrastructure. Experience with Kubernetes (K8S) is a plus. Cloud Expertise: Familiarity with AI infrastructure on AWS and GCP, including Sagemaker, Vertex, Triton, and GPU computing. LLM Deployment: Experience with local (cloud) deployment of OpenSource LLM, like LLAMA, DeepSeek. Bonus Points: Experience with Airbyte and Elastic Search is a significant More ❯

with an interest in exploring other languages. You have experience deploying ML and AI solutions in production on cloud platforms, working with cross-functional teams. Experience with AzureML or SageMaker is highly valued. You possess strong communication skills and experience presenting to clients and managing stakeholders. What does 'Get The Future You Want' mean for you? We promote a More ❯

CloudFormation or Terraform Monitoring and performance tuning of cloud-based applications and services Nice to haves: (MLOps): Model Deployment & Serving – Deploy and manage ML models using MLflow, Azure ML, SageMaker, or similar, ensuring scalability and performance. Monitoring & Retraining – Set up model drift detection, performance monitoring, and automated retraining ML Pipelines & CI/CD – Automate end-to-end ML workflows More ❯

Required technical skills: Coding proficiency in Python, and front-end development experience with Javascript/React. Proficiency development with services such as AWS Lambda, Step Functions, DynamoDB, AppSync, Bedrock, SageMaker, and CloudWatch. Proficiency in developing and integrating with REST-based or GraphQL-based APIs. Proficiency in developing infrastructure-as-code deployment solutions such as AWS CloudFormation or AWS CDK More ❯

performing data science teams. Excellent stakeholder management and communication skills – able to explain complex concepts in accessible language. Proficiency in tools such as Azure ML Studio , Databricks , AWS/SageMaker , Snowflake , and cloud-native platforms. Familiarity with CI/CD tools like Azure DevOps Pipelines or GitHub Actions . Comfortable working in Agile environments and contributing to iterative product More ❯

data science teams. Ability to build and communicate complex solutions to stakeholders across different levels and disciplines. Proficiency working with modern cloud-based tools (e.g., Azure ML , Databricks , Snowflake , SageMaker , etc.). Deep knowledge of machine learning techniques including predictive modelling, pattern recognition, and optimisation. Strong stakeholder management and product ownership skills. Experience with CI/CD tools such More ❯

. Deep technical understanding of AI/ML concepts: supervised and unsupervised learning, GenAI, LLMs, embeddings, MLOps, vector search. Experience designing solutions using tools such as Azure ML, AWS SageMaker, Google Vertex AI, Databricks, LangChain, and Hugging Face. Ability to develop architecture artefacts (e.g., HLDs), estimate effort and cost, and contribute to proposal writing. Strong storytelling and presentation skills More ❯

at Lyst. We work mainly in Python using all the standard ML toolkits and frameworks (e.g. SKLearn, Tensorflow, Pytorch), and run our ML code in the AWS environment using Sagemaker where possible. We have a strong preference for clean, documented, well tested and reviewed code and have tooling and a culture to support this. This is a hands-on More ❯