Job ID: Amazon Web Services Australia Pty Ltd Are you a Senior Cloud Architect with GenAI consulting specialist? Do you have real-time Data Analytics, Data Warehousing, Big Data, Modern Data Strategy, Data Lake, Data Engineering and GenAI experience? Do you have senior stakeholder engagement experience to support pre-sales and deliver consulting engagements? Do you like to solve … Vetting Agency clearance (see ). 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, Amazon Quicksight and Amazon Bedrock. Solutions: Support pre-sales and 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 use of AWS services to support new distributed computing More ❯
Overview The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery Consultant to join our team at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer … robust and scalable AI solutions for business problems Interact with customers directly to understand the business problem, assist in the implementation of their ML ecosystem Leverage Foundation Models on Amazon Bedrock and AmazonSageMaker to meet performance needs Analyze large historical data to automate and optimize key processes Communicate clearly with attention to detail, translating rigorous mathematical … CV, GNN, or distributed training Ability to create compelling customer proposals and present to executives; proficient English communication in technical and business settings Preferred Qualifications Experience with AWS services (AmazonSageMaker, Amazon Bedrock, EMR, S3, EC2); AWS Certification (Solutions Architect Associate, ML Engineer Associate) preferred Knowledge of AI/ML, generative AI; hands-on prompt engineering and More ❯
Delivery Consultant - AI/ML, Professional Services Job ID: AWS EMEA SARL (UK Branch) The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery Consultant to join our team at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS solutions that meet their technical … solutions for business problems Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem Effectively use Foundation Models available on Amazon Bedrock and AmazonSageMaker to meet our customer's performance needs Analyze and extract relevant information from large amounts of historical data to help automate and optimize … candidates to apply. If your 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 why customers from the most More ❯
facing technical role such as Solutions Engineer, Sales Engineer, Developer Advocate, or Technical Consultant. You have deep experience with the AWS ecosystem and services relevant to ML, such as SageMaker, EC2, S3, IAM, and VPC. You are familiar with deep-learning frameworks like PyTorch or JAX, and libraries from the AI ecosystem like Hugging Face Transformers. You have worked More ❯
experience with cloud-native development (GCP preferred). Hands-on experience with GCP Vertex AI (model endpoints, pipelines, embeddings, vector search) or equivalent cloud-native ML platforms (e.g. AWS SageMaker, Azure ML) and agent orchestration frameworks such as LangChain and LangGraph Solid understanding of MLOps - CI/CD, IaC (Terraform), experiment tracking, model registry, and monitoring. Proven experience deploying More ❯
enterprise deployment. Work with cutting-edge ML technologies while ensuring scalable production systems for our global client base. WHAT YOU'LL DO ✅ Deploy ML models as microservices using AWS (SageMaker, Bedrock, Glue) ✅ Build secure APIs with Apigee for enterprise AI access ✅ Manage complete MLOps lifecycle: training → monitoring → drift detection ✅ Develop CI/CD pipelines and mentor client teams ✅ Work More ❯
comfort with AWS, Docker, Terraform/CDK, Postgres, etc. • Solid grounding in ML algorithms, MLOps, and data science workflows. • Experience with Spark, TensorFlow, Kafka, or similar tools. • Experience with SageMaker, KServe, Triton, or similar infra. Nice-to-Have: • Built agentic workflows/LLM tool-use. • Experience with MLFlow, WandB, LangFuse, or other MLOps tools. • Experience with React, FastAPI, or More ❯
comfort with AWS, Docker, Terraform/CDK, Postgres, etc. • Solid grounding in ML algorithms, MLOps, and data science workflows. • Experience with Spark, TensorFlow, Kafka, or similar tools. • Experience with SageMaker, KServe, Triton, or similar infra. Nice-to-Have: • Built agentic workflows/LLM tool-use. • Experience with MLFlow, WandB, LangFuse, or other MLOps tools. • Experience with React, FastAPI, or More ❯
comfort with AWS, Docker, Terraform/CDK, Postgres, etc. • Solid grounding in ML algorithms, MLOps, and data science workflows. • Experience with Spark, TensorFlow, Kafka, or similar tools. • Experience with SageMaker, KServe, Triton, or similar infra. Nice-to-Have: • Built agentic workflows/LLM tool-use. • Experience with MLFlow, WandB, LangFuse, or other MLOps tools. • Experience with React, FastAPI, or More ❯
london (city of london), south east england, united kingdom
Plexe AI
comfort with AWS, Docker, Terraform/CDK, Postgres, etc. • Solid grounding in ML algorithms, MLOps, and data science workflows. • Experience with Spark, TensorFlow, Kafka, or similar tools. • Experience with SageMaker, KServe, Triton, or similar infra. Nice-to-Have: • Built agentic workflows/LLM tool-use. • Experience with MLFlow, WandB, LangFuse, or other MLOps tools. • Experience with React, FastAPI, or More ❯
comfort with AWS, Docker, Terraform/CDK, Postgres, etc. • Solid grounding in ML algorithms, MLOps, and data science workflows. • Experience with Spark, TensorFlow, Kafka, or similar tools. • Experience with SageMaker, KServe, Triton, or similar infra. Nice-to-Have: • Built agentic workflows/LLM tool-use. • Experience with MLFlow, WandB, LangFuse, or other MLOps tools. • Experience with React, FastAPI, or More ❯
About Amazon Web Services Since 2006, Amazon Web Services has been the world's most comprehensive and broadly adopted cloud. AWS has been continually expanding its services to support virtually any workload, and it now has more than 240 fully featured services for compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT … challenges, then craft innovative solutions that accelerate their success. This customer-first approach is how we built the world's most adopted cloud. Join us and help us grow. Amazon Web Services came to China in 2013, and has been relentlessly investing and expanding our infrastructure and business since then. Amazon Web Services launched its China (Beijing) Region … operated by Sinnet) in September 2016 and its China (Ningxia) Region (operated by NWCD) in December 2017. In 2019, Amazon Web Services added a new region in Hong Kong, making China the only country with three Amazon Web Services regions aside from the U.S. In 2022, Amazon Web Services launched Local Zone in Taipei. Amazon Web More ❯
growth. Requirements: MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. Deep proficiency in Python, SQL and cloud infrastructure Proven experience with AWS, including SageMaker, Lambda, and data services How to Apply: Please register your interest by sending your CV to Emily Burgess via the Apply link on this page More ❯
growth. Requirements: MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. Deep proficiency in Python, SQL and cloud infrastructure Proven experience with AWS, including SageMaker, Lambda, and data services How to Apply: Please register your interest by sending your CV to Emily Burgess via the Apply link on this page More ❯
continuous improvement of model delivery practices. Required Skills & Experience Solid Python engineering background with some experience in ML model deployment Familiarity with AWS services and cloud-based ML deployment (SageMaker experience preferred but not required) Basic understanding of data warehousing concepts and SQL (Snowflake experience a plus) Experience with or willingness to learn CI/CD tooling (e.g. GitHub More ❯
continuous improvement of model delivery practices. Required Skills & Experience Solid Python engineering background with some experience in ML model deployment Familiarity with AWS services and cloud-based ML deployment (SageMaker experience preferred but not required) Basic understanding of data warehousing concepts and SQL (Snowflake experience a plus) Experience with or willingness to learn CI/CD tooling (e.g. GitHub More ❯
continuous improvement of model delivery practices. Required Skills & Experience Solid Python engineering background with some experience in ML model deployment Familiarity with AWS services and cloud-based ML deployment (SageMaker experience preferred but not required) Basic understanding of data warehousing concepts and SQL (Snowflake experience a plus) Experience with or willingness to learn CI/CD tooling (e.g. GitHub More ❯
continuous improvement of model delivery practices. Required Skills & Experience Solid Python engineering background with some experience in ML model deployment Familiarity with AWS services and cloud-based ML deployment (SageMaker experience preferred but not required) Basic understanding of data warehousing concepts and SQL (Snowflake experience a plus) Experience with or willingness to learn CI/CD tooling (e.g. GitHub More ❯
london (city of london), south east england, united kingdom
NewDay
continuous improvement of model delivery practices. Required Skills & Experience Solid Python engineering background with some experience in ML model deployment Familiarity with AWS services and cloud-based ML deployment (SageMaker experience preferred but not required) Basic understanding of data warehousing concepts and SQL (Snowflake experience a plus) Experience with or willingness to learn CI/CD tooling (e.g. GitHub More ❯
for a Data Engineer for FS domain with Machine learning and MLOps background and proficiency in Python. YOUR PROFILE Primary Skill: AWS Data Engineering, ML Engineering, ML-Ops, ECS, Sagemaker, Gitlab, Jenkins, CI/CD, AI Lifecycle, Experience in front-end development (HTML, Stream-lit, Flask.) Familiarity with model deployment and monitoring in cloud environments (AWS). Understanding of More ❯
