20 of 20 Remote Amazon SageMaker Jobs

Learning Engineer to join the growing data science and AI team. You'll play a key role in designing, developing, and deploying scalable machine learning solutions using Python and Amazon SageMaker . This role is based UK Wide. This role will be Via Umbrella. Working in a Hybrid Model of 1 day a week on site. Key Responsibilities … Design and implement machine learning models for classification, regression, and forecasting tasks. Build and manage end-to-end ML pipelines using Amazon SageMaker . Collaborate with data scientists, engineers, and product teams to integrate ML solutions into production systems. Optimise model performance and scalability. Monitor and maintain deployed models, ensuring reliability and accuracy. Stay up-to-date with … research and tools. Required Skills & Experience Strong proficiency in Python and its ML/data libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow or PyTorch). Hands-on experience with Amazon SageMaker , including training, tuning, and deploying models. Solid understanding of machine learning algorithms and statistical methods. Experience with cloud platforms (AWS preferred). Familiarity with CI/CD More ❯

certification desirable). Proven experience deploying and supporting LLMs in production. Strong understanding of LLM fine-tuning (PyTorch, TensorFlow, Hugging Face Trainer, etc.). Experience with ML tooling (e.g. SageMaker, LangChain/LangSmith, MLflow, Dataiku, DataRobot). Knowledge of embeddings, their applications, and limitations. Hands-on experience in Agile/Lean/XP environments. Excellent communication, problem-solving, and More ❯

certification desirable). Proven experience deploying and supporting LLMs in production. Strong understanding of LLM fine-tuning (PyTorch, TensorFlow, Hugging Face Trainer, etc.). Experience with ML tooling (e.g. SageMaker, LangChain/LangSmith, MLflow, Dataiku, DataRobot). Knowledge of embeddings, their applications, and limitations. Hands-on experience in Agile/Lean/XP environments. Excellent communication, problem-solving, and More ❯

retrieval techniques (nice to have). - Familiarity with DevOps tooling (Docker, Kubernetes, Terraform) or infrastructure-as-code practices (nice to have). - Exposure to MLOps frameworks (MLflow, DVC, Kubeflow, SageMaker) (nice to have). ECCO Select is committed to hiring and retaining a diverse workforce. Our policy is to provide equal opportunity to all people without regard to race 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 ❯

intensive applications, including processing unstructured text, integrating with databases (e.g., Pinecone, Weaviate), or handling multimodal inputs like images for OCR-enhanced workflows. Experience with other cloud platforms (e.g., AWS SageMaker, Azure ML) alongside GCP, including containerization with Docker and orchestration via Kubernetes. Contributions to open-source LLM projects, hackathons, or publications showcasing innovative uses of models like GPT-series More ❯

Collaborate closely with data scientists and software engineers to productionize prototypes into scalable, maintainable solutions. Essential Skills & Experienc: • Hands-on experience with ML Ops tools such as MLflow, Kubeflow, Amazon SageMaker, Vertex AI, orequivalent platforms. • Deep understanding of cloud infrastructure services (AWS, Azure, GCP). • Strong experience with CI/CD practices and containerization tools (Docker, Kubernetes). 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 ❯

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 ❯

Bonus Points For Prior consulting experience in a top-tier firm or internal transformation role within Financial Services Familiarity with AI tools or platforms such as Azure AI, AWS SageMaker, or TensorFlow Hands-on experience implementing AI use cases in regulated environments Knowledge of frameworks like NIST AI RMF, ISO 38507, or DAMA DMBOK Relevant certifications in Responsible AI More ❯

and ML engineers to reduce time-to-production for experiments and prototypes. Design and optimize data wrangling and transformation workflows using Python. Leverage AWS cloud services (EC2, S3, Lambda, SageMaker, RDS, DynamoDB, Redshift, etc.) to build robust, scalable, and cost-effective solutions. Apply AIOps practices to enhance monitoring, automation, and resilience of ML systems. Implement best practices in data … software engineering principles. Advanced proficiency in Python for data wrangling, pipeline automation, and ML workflows. Expertise in AWS services, including databases (RDS, DynamoDB, Redshift) and machine learning/AI (SageMaker, AI/ML frameworks). Hands-on experience with ML pipeline orchestration, CI/CD, and deployment automation. Deep understanding of ML Ops practices, including monitoring, scaling, and retraining More ❯

applications (e.g., chatbots, summarization tools, recommendation engines). • Knowledge of application compatibility, security, and performance optimization. • Familiarity with AWS services related to frontend deployment and GenAI model hosting (e.g., SageMaker, Bedrock). Preferred Skills: • Experience with Angular and hybrid frontend architectures. • Exposure to CI/CD pipelines and cloud-native development practices. • Familiarity with GenAI frameworks and libraries (e.g. More ❯

applications (e.g., chatbots, summarization tools, recommendation engines). • Knowledge of application compatibility, security, and performance optimization. • Familiarity with AWS services related to frontend deployment and GenAI model hosting (e.g., SageMaker, Bedrock). Preferred Skills: • Experience with Angular and hybrid frontend architectures. • Exposure to CI/CD pipelines and cloud-native development practices. • Familiarity with GenAI frameworks and libraries (e.g. More ❯

applications (e.g., chatbots, summarization tools, recommendation engines). • Knowledge of application compatibility, security, and performance optimization. • Familiarity with AWS services related to frontend deployment and GenAI model hosting (e.g., SageMaker, Bedrock). Preferred Skills: • Experience with Angular and hybrid frontend architectures. • Exposure to CI/CD pipelines and cloud-native development practices. • Familiarity with GenAI frameworks and libraries (e.g. More ❯

other language services Expert in Machine Learning, Modeling, and development with Python Expert in MLOps with at least one platform, e.g.: MLflow, Kubeflow, or end-to-end automation with SageMaker services Ability to mentor others and work independently Nice to Have Production experience with any of the following is a plus: GenAI, LLMs, Recommendation Engines, AWS offerings for AI … and ML including SageMaker, Bedrock, Lex Knowledge of relevant regulations in AI/ML and incorporating compliance into MLOps processes Bachelor's degree or higher in computer science, engineering, or information systems Veeva's headquarters is located in the San Francisco Bay Area with offices in more than 15 countries around the world. As an equal opportunity employer, Veeva More ❯

Description 9 Months Fixed Term Contract The Data Science role is responsible for using Data Science and modelling techniques to address critical questions for both the business and our customers. This includes understanding the challenges our customers face with regards More ❯

Description 9 Months Fixed Term Contract The Data Science role is responsible for using Data Science and modelling techniques to address critical questions for both the business and our customers. This includes understanding the challenges our customers face with regards More ❯

facing role blends data analyst and data engineer skills, including requirement gathering, stakeholder communication, and delivering robust data solutions. Hands-on experience with Power BI, Sisense, Quicksight, and AWS (Sagemaker Unified Studio preferred) is highly desirable. Offering a competitive salary, performance-based bonuses, and fully flexible remote working, this is a fantastic opportunity to shape and lead analytics projects … analysis, cleansing, enrichment, metadata management, and data innovation. Proficiency in SQL and MySQL. Experience with business intelligence tools: Power BI, Sisense, Quicksight. Hands-on experience with ETL tools, ideally Sagemaker Unified Studio. Ability to validate, test, and build data engineering solutions. Strong communication skills with ability to translate between technical and non-technical stakeholders. Desirable 2-5 years' client More ❯

facing role blends data analyst and data engineer skills, including requirement gathering, stakeholder communication, and delivering robust data solutions. Hands-on experience with Power BI, Sisense, Quicksight, and AWS (Sagemaker Unified Studio preferred) is highly desirable. Offering a competitive salary, performance-based bonuses, and fully flexible remote working, this is a fantastic opportunity to shape and lead analytics projects … analysis, cleansing, enrichment, metadata management, and data innovation. Proficiency in SQL and MySQL. Experience with business intelligence tools: Power BI, Sisense, Quicksight. Hands-on experience with ETL tools, ideally Sagemaker Unified Studio. Ability to validate, test, and build data engineering solutions. Strong communication skills with ability to translate between technical and non-technical stakeholders. Desirable 2-5 years' client More ❯