1 to 25 of 99 Amazon SageMaker Jobs

Job ID: AWS EMEA SARL (Italy Branch) At Amazon, we are continuously striving to be the most customer-centric company in the world. AWS has been helping over one million customers in over 190 countries to deliver flexibility, scalability, and reliability across their organizations. Behind this success are exceptionally … talented, bright, and driven individuals who work hard, have fun, and make history. As a Solution Architect within Amazon Web Services (AWS), you will have the opportunity to help shape and deliver on a strategy to build mind share and broad use of Amazon's services (like Amazon Bedrock, Amazon Q, Amazon SageMaker, Amazon DynamoDB, Amazon S3, Amazon EC2, and Amazon SQS, etc.) within strategic accounts across Italy. Your broad responsibilities will include: owning the technical engagement and ultimate success around specific implementation projects, and developing deep expertise in the more »

Associate Data Analytics Consultant, A2C Do you enjoy leading, guiding, and influencing customers and team members to build data analytics solutions? At Amazon Web Services, we're hiring highly technical Data Analytics Consultants to collaborate with our customers and partners on key customer engagements. You will apply your deep … the combination of cultural philosophies, practices, and tools that deliver end-to-end applications and infrastructure solutions. You will join as part of the Amazon Web Services Professional Services (ProServe) Associate to Consultant (A2C) practice, which focuses on the accelerated career development of university graduates and early career professionals. … on projects. The ideal candidate will have extensive experience with design, development and operations that leverages deep knowledge in the use of services like Amazon Kinesis, Apache Kafka, Apache Spark, Amazon SageMaker, Amazon EMR. The Data Analytics Consultant is comfortable rolling up their sleeves to design more »

Machine Learning Engineer, Amazon Music Search As a machine learning engineer on the Amazon Music Search team, you will collaborate with scientists on developing and evaluating machine learning models (Search Relevancy & Ranking) using large datasets such as meta-data and search queries to improve the customer experience through … ideate, experiment, iterate, optimize, and scale quickly while thoughtfully balancing speed and quality. Key Job Responsibilities Use ML and Generative AI tools, such as Amazon SageMaker and Amazon Bedrock, to provide scalable production solutions to improve the customer experience, label data, build, train, tune, and deploy models. … help automate and optimize key processes. Work closely with science and engineering teams to drive model implementations and develop new algorithms. About the Team Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams more »

System Development Engineer II- AWS, Sales Tech , Amazon - SalesTech Amazon Seller Services India offers innovative solutions to help sellers grow their online businesses. With a fast-paced, entrepreneurial work environment, you'll be at the heart of Amazon's drive to deliver cutting-edge cloud technologies. We … highly available AWS cloud infrastructure. Design, build, and optimize scalable solutions for data generation and processing, improving the quality and performance of models. Use Amazon Bedrock and Amazon SageMaker to support the development, training, tuning, and deployment of machine learning models. Collaborate with product and engineering teams … Experience with CI/CD pipelines build processes PREFERRED QUALIFICATIONS Experience with distributed systems at scale Posted: February 12, 2025 (Updated 1 day ago) Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race more »

Azure. Experience with business intelligence tools like Tableau or PowerBI. Experience working with LLMs. Experience working with AWS Services like EC2, RDS(Postgres), SQS, Sagemaker, MLflow, S3, API gateway, ECS. Experience in UI frameworks like VueJS is a plus. About Us FactSet creates flexible, open data and software solutions more »

e.g., AWS, GCP, Azure) and their AI/ML services. Big data technologies (e.g., ElasticSearch, Athena, vector DBs). MLOps practices and tools (e.g., SageMaker). The estimated base salary range for this position is $160,000 to $250,000, which is specific to New York and may change more »

transformers. Experience working with large-scale datasets, data augmentation, and feature extraction techniques. Proficiency in cloud computing services for AI/ML deployment (AWS SageMaker, Azure ML, GCP AI). Familiarity with MLOps practices, including model versioning, deployment, and monitoring. Strong problem-solving skills and ability to work in more »

transformers. Experience working with large-scale datasets, data augmentation, and feature extraction techniques. Proficiency in cloud computing services for AI/ML deployment (AWS SageMaker, Azure ML, GCP AI). Familiarity with MLOps practices, including model versioning, deployment, and monitoring. Strong problem-solving skills and ability to work in more »

a programming challenge during the interview process. Experience with Jupyter Notebooks, Python Data Science Libraries. Experience with ML-OPS and related tools (e.g., MLFLOW, Sagemaker, Bedrock) and ability to build interactive, insightful dashboards for monitoring ML models. Place of Performance: Hybrid work in San Antonio, TX. Desired Skills (Optional more »

staying at the forefront of technology, digital and AI advancements. Experience creating impactful slide decks and communicating data Good-to-Have Skills: Pytorch/Sagemaker/GreenGrass or equivalent technologies. Experience with GMP background Experience with DevOps and MLOps pipelines for training and maintenance of vision models Experience with more »

can avoid asking you about something you don't know about as we get to know each other. AWS services : EC2, Lambda, API Gateway, SageMaker, S3 (or equivalent from Azure, Google Cloud) Programming languages : Python, C++ Deep Learning Frameworks : PyTorch, TensorFlow, CUDA DevOps and automation, testing : Terraform, Ansible, Pytest more »

DevOps tools. Software engineering, cloud computing, data management, and system integration Machine learning frameworks such as TensorFlow, PyTorch, and deploying models in cloud environments (SageMaker) data engineering and feature engineering for big data processing and machine learning algorithms. Understanding cloud platforms (AWS, OCI, Azure, or GCP) and best practices more »

DevOps tools. Software engineering, cloud computing, data management, and system integration Machine learning frameworks such as TensorFlow, PyTorch, and deploying models in cloud environments (SageMaker) data engineering and feature engineering for big data processing and machine learning algorithms. Understanding cloud platforms (AWS, OCI, Azure, or GCP) and best practices more »

DevOps tools. Software engineering, cloud computing, data management, and system integration Machine learning frameworks such as TensorFlow, PyTorch, and deploying models in cloud environments (SageMaker) data engineering and feature engineering for big data processing and machine learning algorithms. Understanding cloud platforms (AWS, OCI, Azure, or GCP) and best practices more »

DevOps tools. Software engineering, cloud computing, data management, and system integration Machine learning frameworks such as TensorFlow, PyTorch, and deploying models in cloud environments (SageMaker) data engineering and feature engineering for big data processing and machine learning algorithms. Understanding cloud platforms (AWS, OCI, Azure, or GCP) and best practices more »

DevOps tools. Software engineering, cloud computing, data management, and system integration Machine learning frameworks such as TensorFlow, PyTorch, and deploying models in cloud environments (SageMaker) data engineering and feature engineering for big data processing and machine learning algorithms. Understanding cloud platforms (AWS, OCI, Azure, or GCP) and best practices more »

DevOps tools. Software engineering, cloud computing, data management, and system integration Machine learning frameworks such as TensorFlow, PyTorch, and deploying models in cloud environments (SageMaker) data engineering and feature engineering for big data processing and machine learning algorithms. Understanding cloud platforms (AWS, OCI, Azure, or GCP) and best practices more »

with frameworks such as FastAPI, TensorFlow, LangChain/LlamaIndex. Familiarity with prompt engineering, embeddings & RAG, and vector databases. Experience with AWS ML capabilities (e.g. SageMaker, Bedrock) or their GCP/Azure equivalents. Experience with evaluating and improving the accuracy, efficiency and performance of LLM and RAG implementations and use more »

agents, and frameworks like vLLM, to drive product innovation. Utilize strong Python skills and work with tools like GitHub, Docker, SQL, PyTorch, and AWS Sagemaker to develop scalable solutions. Participate in a dynamic, fast-paced environment that offers opportunities for professional growth and product ownership. Work closely with a more »

FADE/MIST, ECO/ETAS. Strong programming skills in Python, SQL, and experience with version control systems like Git. Familiarity with GIMS, AWS Sagemaker, AWS Cloud, and ESRI ArcGIS. Competency in statistical analysis, including descriptive and Bayesian statistics, Markov-Chain modeling, and machine learning frameworks like TensorFlow. Knowledge more »

computing, data management, and system integration 11.(Desired) Demonstrated experience with machine learning frameworks such as TensorFlow, PyTorch, and deploying models in cloud environments (SageMaker) 12.(Desired) Demonstrated experience with data engineering and feature engineering for big data processing and machine learning algorithms. 13.(Desired) Demonstrated experience with understanding more »

with data visualization platforms such as PowerBI, Tableau or Sigma Knowledge of any of the following tools is a plus: Databricks, Snowflake, Dataiku, AWS, Sagemaker Oil and gas industry experience is a plus We are actively seeking candidates for full-time, remote work within the US and UK. Atlanta more »

computing, data management, and system integration 15.(Desired) Demonstrated experience with machine learning frameworks such as TensorFlow, PyTorch, and deploying models in cloud environments (SageMaker) 16.(Desired) Demonstrated experience with data engineering and feature engineering for big data processing and machine learning algorithms. 17.(Desired) Demonstrated experience with understanding more »

help, but aren't essential: Familiarity with cloud Knowledge of Infrastructure as Code (Terraform, Terragrunt) Tech Stack: Clickhouse DBT Airflow Terraform, Terragrunt, Helm AWS Sagemaker Bedrock Gitlab CI DVC MLFlow/Kubeflow/Weights & Biases About us: FXC Intelligence is a leading provider of cross-border payments data and more »

Have: Experience with deploying analytics workloads on platform as a service ( PaaS ) and sof tware as a service ( SaaS ) , including AWS EMR, Redshift, or SageMaker or Azure Databricks, SQL Data Warehouse, or Machine Learning service Experience with distributed or parallel programming frameworks, including Apache Spark or NVIDIA CUDA, and more »