help them achieve business outcomes with AWS. Our projects are often unique, one-of-a-kind endeavors that no one has done before. At Amazon Web Services (AWS), we are helping large enterprises build AI solutions on the AWS Cloud. We apply predictive technology to large volumes of data … our customers. You will leverage the global scale, elasticity, automation, and high-availability features of the AWS platform. You will build customer solutions with AmazonSageMaker, Amazon Bedrock, Amazon Elastic Compute (EC2), Amazon Data Pipeline, Amazon S3, Glue, Amazon DynamoDB, Amazon Relational … Database Service (RDS), Amazon Elastic Map Reduce (EMR), Amazon Kinesis, AWS Lake Formation, and other AWS services. You will collaborate across the whole AWS organization, with other consultants, customer teams, and partners on proof-of-concepts, workshops, and complex implementation projects. You will innovate and experiment to help More ❯
the latest data analytics technologies? Would you like a career path that enables you to progress with the rapid adoption of cloud computing? At Amazon Web Services, we're hiring highly technical cloud architect specialised in data analytics to collaborate with our customers and partners to derive business value … Key job responsibilities Expertise - Collaborate with pre-sales and delivery teams to help partners and customers learn and use services such as AWS Glue, Amazon S3, Amazon DynamoDB, Amazon Relational Database Service (RDS), Amazon Elastic Map Reduce (EMR), Amazon Kinesis, Amazon Redshift, Amazon Athena, AWS Lake Formation, Amazon DataZone, AmazonSageMaker and Amazon Quicksight. Solutions - Deliver technical engagements with partners and customers. This includes participating in pre-sales visits, understanding customer requirements, creating consulting proposals and creating packaged data analytics service offerings. Delivery - Engagements include projects proving the More ❯
career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's … experience with model customization techniques such as fine-tuning, continued pre-training, and LLM-as-judge evaluation - Experience with optimization of models on GPUs, Amazon Silicon, or TPUs, also experience with open source frameworks for building applications powered by LLMs like LangChain, LlamaIndex, and/or similar tools - Experience … building generative AI applications on AWS using services such as Amazon Bedrock and AmazonSageMakerAmazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value More ❯
potential and challenges of GenAI models and applications to engineering teams and C-Level executives. This requires deep familiarity across the stack - compute infrastructure (Amazon EC2, Amazon EKA), ML frameworks PyTorch, JAX, orchestration layers Kubernetes and Slurm, parallel computing (NCCL, MPI), MLOPs, through to AmazonSageMaker Hyperpod, Amazon Bedrock as well as target use cases in the cloud. This is an opportunity to be at the forefront of technological transformations, as a key technical leader. Additionally, you will work with the AWS Generative AI and EC2 product teams to shape product vision and prioritize … career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's 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 ❯
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, AWS 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. At Rakuten Viber, we connect people-no matter who they are, or where they are from. As 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 ❯
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 ❯
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 ❯
Planning Analytics View more categories View less categories Sector Data Science ,Technology Role Analyst Contract Type Permanent Hours Full Time DESCRIPTION The goal of Amazon Logistics (AMZL) is to build a world class last mile operation. Amazon aims to exceed the expectations of our customers by ensuring that … tools experience: Quicksight/Tableau or similar tools 3. Scripting Experience: R/Python/C++ 4. (Optional) Experience with AWS solutions (S3, Athena, Sagemaker) Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions … priority for Amazon. Please consult our Privacy Notice () to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive 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, Azure 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 unsupervised learning techniques Experience in demand prediction, optimisation, or computer vision is advantageous Comfortable working with cloud platforms (preferably AWS) and services like SageMaker or Lambda Strong mathematical and statistical foundations, with a sharp eye for patterns and insights Willingness to build basic backend development skills (Python/ More ❯
down complex challenges, devise practical solutions, and iterate quickly based on feedback or data. Hands-on experience with cloud platforms, including AWS (e.g., EC2, Sagemaker, Bedrock, S3, Lambda), Google Cloud (e.g., Compute Engine, Vertex, GKE, BigQuery), Azure (e.g., Virtual Machines, Azure OpenAI) etc. Proficiency in scripting or programming (e.g. More ❯
especially in deploying AI models or microservices. Cloud Services: Familiarity with cloud platforms like AWS, Azure, or GCP. Experience with services such as AWS SageMaker, Google AI, or Azure Machine Learning is a plus. Serverless Architectures: Exposure to serverless architectures, ideally edge compute environments such as Cloudflare Workers. Problem More ❯
data versioning, quality management, and CI/CD pipelines Experience with cloud platforms (e.g., AWS or Azure) and data tools such as Terraform or SageMaker is a plus Ideally, some hands-on experience building and maintaining data pipelines in a production environment What's on Offer: Competitive salary More ❯
FCA PS21/3, DORA, NIST AI RMF). Experience working with AI/ML platforms and monitoring tools (e.g., MLflow , Azure ML, SageMaker , Databricks , Python etc ). Excellent stakeholder management and communication skills. Desirable: Technical background in AI/ML, data science, or software engineering Experience with cloud More ❯
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 More ❯
applications. Full-stack development experience with AI technologies/tools and apply it to user experiences or backend solutions. Experience with AI technologies like SageMaker, Vert.x, LangChain, Large Language Models, Prompt Engineering, DialogFlow, Python. Experience with at least one of the following: Front-end technologies like React, Angular, SwiftUI More ❯
Segment Commercial Tooling: Hubspot, Planhat, Intercom Company & Customer Analytics: Looker AI Tools & Frameworks: (to be built upon) TensorFlow/PyTorch for model development. AWS SageMaker or Vertex AI for scalable model deployment. OpenAI APIs or Hugging Face for generative AI applications. What are the benefits? People are our core More ❯
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 More ❯
data. Understand the PMML and ONNX model portability standards. Have experience with Teradata partner's analytical products, Cloud Service providers such as AzureML and Sagemaker and partner products such as Dataiku and H2O. Have strong hands-on programming skills in at least one major analytic programming language and/ More ❯
Delivery Practice Manager - Data Analytics, ASEAN Professional Services, ASEAN Professional Services Job ID: PT Amazon Web Services Indonesia - E41 The Amazon Web Services Professional Services (ProServe) team is seeking an experienced Delivery Practice Manager (DPM) to join our ProServe Shared Delivery Team (SDT) at Amazon Web Services … the ability to translate technical concepts into business value for customers and then talk in technical depth with teams, you will cultivate strong customer, Amazon Global Sales (AGS), and ProServe team relationships which enables exceptional business performance. DPMs success is primarily measured by consistently delivering customer engagements by supporting … career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's More ❯
