1 to 25 of 33 Amazon SageMaker Jobs

Diversity and Inclusion. Role : Machine Learning engineer Key Responsibilities Work with our customers and focus on our AWS Analytics and ML service offerings such Amazon Kinesis, AWS Glue, Amazon Redshift, Amazon EMR, Amazon Athena, Amazon Sagemaker and more. Help our customers to remove the … Solution Architects, Data Scientists and Service Engineering teams 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, NoSQL technologies and other 3rd parties Develop and define key business questions … and implement them as part of data pipeline IT platform implementation experience Experience with one or more relevant tools ( Flink, Spark, Sqoop, Flume, Kafka, Amazon Kinesis) Experience developing software code in one or more programming languages (Java, JavaScript, Python, etc) Current hands-on implementation experience required Preferred Qualifications Masters more »

Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark more »

Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark more »

Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark more »

Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark more »

Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark more »

Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark more »

Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark more »

Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark more »

to life for business stakeholders and equally convey business needs effectively to technical audiences. Knowledge in working with at least one cloud platform AWS (SageMaker), GCP (Vertex AI), Azure (Azure ML). A growth mindset - Ability to assess the value Machine Learning brings to the business. An excellent understanding more »

using Python and the AWS Cloud Development Kit. You'll use a variety of services such as SNS, SQS and Lambda for event streams, Amazon Redshift, S3 and AWS Glue for data storage & reporting and Amazon SageMaker for our pioneering machine learning products. We are a growing … work with our colleagues across ECS to help them use our services. Python andAWS Services such as S3, Kinesis, Lambda, Redshift, DynamoDB, Glue and SageMaker Infrastructure-as-Code tools and approaches (we use the AWS CDK with CloudFormation) Data processing frameworks such as pandas, Spark and PySpark Machine learning more »

Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment. Proficient in big data technologies such as Hadoop, Spark, and Kafka for handling large datasets. more »

Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment. Proficient in big data technologies such as Hadoop, Spark, and Kafka for handling large datasets. more »

Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment. Proficient in big data technologies such as Hadoop, Spark, and Kafka for handling large datasets. more »

ideas to diverse audiences. Ability to work in a collaborative team environment and manage multiple projects simultaneously. Experience working with the AWS + Services (Sagemaker or equivalent) Desirables: A financial technology background Experience with SQS or Kafka Prior work with CI/CD tools Prior work with a transformation more »

engineering practices sch as CI/CD. Experience deploying/monitoring machine learning models and following best practices. The Ability to develop pipelines using SageMaker, MLFlow or similar frameworks. Strong experience with data programming frameworks such as Apache Spark. Understanding of common Data Science and Machine Learning models, libraries more »

models to build a better future where a new job is just a click away. Your responsibilities: Implement and productionise ML-based services using Sagemaker Collaborate with Data Scientists to design and implement LLM-based inference workflows Utilize IaC and CI/CD best practices to increase efficiency in … years of experience in Machine Learning Engineering, Data Engineering, or a related field Proficiency in production-level Python (Clean, SOLID) and industry experience with Amazon Sagemaker deployment of LLMs Experience with LLM-related packages, such as PyTorch, Transformers etc. Experience with IaC (Terraform), CI/CD, and test more »

deploying industrial grade AI solutions •Experience in using AI frameworks, trending models and libraries, such as TensorFlow, PyTorch, GPT, Gemini, LaMDA, LangChain, Vertex AI, SageMaker, etc •Experience in using cloud services and platforms, such as GCP, AWS, etc •Enthusiasm, strong analytical mind, willingness to learn and desire to make more »

leading a data science team and managing complex projects. Expertise in machine learning, statistics, data management, and relevant technologies (e.g., Python, R, SQL, AWS SageMaker, Apache Airflow, Dbt, AWS Kinesis). Strong communication skills with the ability to explain complex data concepts to a non-technical audience. Knowledge of more »

/Python-based REST APIs, and API specifications using Swagger/OpenAP Functional programming and object-orientated programming AWS services (including Kinesis, ECR, Lambdas, SageMaker and DynamoDb) or other cloud services Sound understanding of risk and risk mitigation design in relevant areas, including (but not limited to) fraud, financial more »

or equivalent experience. Experience creating LLM & RAG driven applications. Proficiency in programming with tools like Python, TensorFlow, and PyTorch. ML Deployment with services like Sagemaker, AzureML, VertexAI etc. A keen understanding of AI ethics and responsible AI deployment. Innovative thinking and excellent problem-solving abilities. Desirable skills: Experience with more »

genAI. QualificationsWhat you’ll need:• Technical expertise in tools spanning: data warehousing, ETL, internal visualisation and analytics. Good examples are Snowflake, GCP, Azure Analytics, Sagemaker, Databricks, Tableau, PowerBI, Looker, Quicksight, Airflow, astronomer.io, Alteryx, Collibra.• Hands on experience and\or a detailed and deep understanding of the workflow and approaches more »

Scientists and Software Engineers to develop and productionise a greenfield NLP product. Experience required (min. 5 years): NLP MLOps with Cloud (AWS w/SageMaker preferred, other clouds also considered) End-to-end ML experience Other details: Up to £650 per day outside IR35 3 stage interview process more »

platform is looking for a Principal Data Engineer to take a lead on several aspects of their data platform built in Python, Airflow, Kafka, Sagemaker, AWS and GCP. 💰 Salary: up to £130k + 15% bonus 📍 Location: can be based anywhere in the UK ✅ Must have requirements: Mastery of Python more »

pipelines. This role is critical in ensuring the high performance and reliability of our AI-driven solutions. Responsibilities: Deploy LLMs using platforms like Huggingface, Sagemaker, or similar. Manage deployment on multiple GPUs, ensuring optimal performance. Implement scaling and load balancing to handle varying loads efficiently. Design and maintain data more »