Software Development Engineer II, AWS SageMaker AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in … skilled and innovative Software Development Engineer with a passion for developing new machine learning capabilities and driving innovation to build customer-centric solutions in AmazonSageMaker AI? Are you interested to play a key role in developing software applications at AWS? We invite you to join us and … be part of making history. The AmazonSageMaker Pipelines team is seeking a highly skilled and innovative Software Development Engineer to join our organization. SageMaker Pipelines provides a serverless workflow orchestration capability purpose-built for MLOps/LLMOps automation. This capability enables our customers to easily build More ❯
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 … and cost optimization. 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, AmazonSageMaker, Amazon DynamoDB, Amazon S3, Amazon EC2, and Amazon … how applications and services are constructed using the AWS platform. The ideal candidate will possess customer-facing skills that will allow them to represent Amazon well within a customer's environment and drive discussions with senior personnel within the company, as well as a technical background that enables them More ❯
solutions including Gen AI ensuring scalability, security, governance and cost optimization. Expert level knowledge in MLOps. Expertise in cloud-based AI platforms such as AmazonSageMaker, Amazon Bedrock, Databricks, and Kubernetes. Experience with AWS cloud infrastructure, networking, and IAM services. Proven ability to define AI capability models More ❯
OIDC integration and a deep understanding of OAuth, JWT/JWE/JWS. Solid understanding of backend performance optimization and debugging. Knowledge of AWS SageMaker and data analytics tools. Proficiency in frameworks TensorFlow, PyTorch, or similar. Preferred Qualifications, Capabilities, and Skills: Familiarity with LangChain, Langgraph, or any Agentic Frameworks More ❯
Electrical Engineering, Computer Engineering or related field. Experience in containerization - Docker/Kubernetes. Experience in AWS cloud and services (S3, Lambda, Aurora, ECS, EKS, SageMaker, Bedrock, Athena, Secrets Manager, Certificate Manager etc.). Proven DevOps/MLOps experience provisioning and maintaining infrastructure leveraging some of the following: Terraform, Ansible More ❯
AI/ML tools and frameworks, including Python, PySpark, TensorFlow, PyTorch, Vertex AI, MLflow, and cloud-based ML platforms such as Azure ML, AWS SageMaker, and Google Cloud AI. Experience with production-scale AI/ML pipelines, including data exploration, feature engineering, model training and comparison, bias and fairness More ❯
technologies like Docker, Kubernetes, AWS EKS etc. Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g. AWS Bedrock, AWS S3, AWS Sagemaker, Azure AI search, Azure OpenAI, Azure blob storage etc. Master's degree or above in Machine learning/data science, computer science, applied mathematics More ❯
e.g., Airflow). Leverage expertise in cloud computing platforms (AWS and Azure) to build and optimize AI infrastructure, using services like AWS Bedrock, S3, SageMaker, Azure AI Search, etc. Champion ML governance by ensuring guidelines are followed, monitoring SLAs, and continuously improving the performance and reliability of AI solutions. More ❯
passion for machine learning and investing independent time towards learning, researching, and experimenting with new innovations in the field. Experience working with technologies like SageMaker, Athena/Trino, Spark, Milvus, and OpenSearch. #J-18808-Ljbffr More ❯
accessing and processing data (PostgreSQL preferred but general SQL knowledge is more important). Familiarity with latest Data Science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g. Tensorflow, MXNet, scikit-learn). Knowledge of software engineering practices (coding practices to DS, unit testing, version control, code review). More ❯
Proficiency in programming languages such as Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). What we offer Culture of caring: At GlobalLogic, we prioritize a culture of caring. More ❯
Proficiency in programming languages such as Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). What we offer Culture of caring: At GlobalLogic, we prioritize a culture of caring. More ❯
machines, and neural networks (deep learning experience strongly preferred) Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g., AWS Bedrock, S3, SageMaker; Azure AI Search, OpenAI, blob storage, etc. Bachelor's degree (master's or higher strongly preferred) in machine learning, computer science, data science, applied More ❯
training and model optimization . Experience deploying ML models and LLMs in cloud environments and local environments. Proficiency with AWS infrastructure, including EC2, S3, SageMaker and Bedrock. Ability to build effective ML pipelines for research and development. Experience with ML model lifecycle tools (e.g., MLflow, DVC, Weights & Biases). More ❯
deep learning, computer vision, natural language processing, etc Experience in building ML models in production using AWS ecosystem, especially ML related services such as SageMaker Ability to work independently and collaboratively with multi-functional teams with excellent communication and presentation skill Experience in writing unit tests and documentation for More ❯
Fitch Group, Inc., Fitch Ratings, Inc., Fitch Solutions Group
machines, and neural networks (deep learning experience strongly preferred) Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g., AWS Bedrock, S3, SageMaker; Azure AI Search, OpenAI, blob storage, etc. Bachelor’s degree (master’s or higher strongly preferred) in machine learning, computer science, data science, applied More ❯
Proficiency in programming languages such as Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). What We Offer Culture of Caring: At GlobalLogic, we prioritize a culture of caring. More ❯
Scipy), machine learning modules (Tensorflow or Pytorch, Scikit-Learn), and SQL. Solid technical experience developing ML solutions in a cloud environment (e.g., Vertex AI, Sagemaker); understanding of software engineering principles including version control, code reviews, agile methodology, unit tests; and familiarity with containerisation. Understanding of statistical modeling, machine learning 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 ❯
the RFI/RFP process, as preferred bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn). Cloud platforms - demonstrable experience of building and deploying solutions to Cloud (e.g. AWS More ❯
Data manipulation Data analysis Pandas Experience of large datasets: Clustering, classification Regression machine learning or deep learning Data presentation AWS knowledge: Lambda functions and Sagemaker Exposure to time series data generated by IoT platforms Please note that if you are NOT a passport holder of the country for the More ❯
language models Proven experience with cloud platforms such as AWS, Azure, or Google Cloud Familiarity with tools and frameworks such as TensorFlow, PyTorch, MLflow, SageMaker, or Databricks Deep understanding of data architecture, APIs, and model deployment best practices Knowledge of MLOps and full model lifecycle management Excellent communication and More ❯
and deploying LLM capabilities in production at scale. Strong experience with Python programming and common ML frameworks (e.g., PyTorch, TensorFlow) and MLOps platforms (e.g., SageMaker). Exceptional verbal and written communication skills, with the ability to convey complex technical concepts to diverse audiences. Demonstrated ability to work effectively on 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 ❯
and data science. PhD or MSc in a related subject, Mathematics, Machine Learning, etc. Strong Python, SQL, and cloud-based ML framework expertise (AWS SageMaker, TensorFlow, PyTorch). Experience with real-time data processing. Knowledge of probabilistic modelling, optimisation, A/B testing. Knowledge of AdTech systems. Excellent problem More ❯
