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Senior Full Stack Machine Learning Engineer Join our Artificial Intelligence and Machine Learning product area.
The team comprises data engineers and data scientists who collaborate to deliver AI solutions that automate manual processes within the global financial services and investment sectors.
Responsibilities and Requirements Experience: 8+ years in large-scale, sophisticated systems development, including software development, deployment, API development, UI development, or related areas.
Cloud Skills: 3+ years hands-on experience with AWS services such as S3, EC2, Lambda, AWS Step Functions, SNS, SQS.
Tools and Platforms: Proficiency with CI/CD tools like Jenkins, uDeploy, or Concourse; deploying data pipelines and OLTP systems in AWS using RDS/Postgres or data warehousing tools like Snowflake.
Security and Infrastructure: Experience establishing CI/CD pipelines for AWS or similar cloud providers, understanding IAM roles, policies, security certificates.
Compute and Containerization: Experience with EC2 and EKS for API hosting, containerization with Docker, orchestration with Kubernetes.
API Development: Proven experience with Java (Spring Boot) and/or Python microservices, including deployment.
Data Skills: Strong SQL skills; experience analyzing data across platforms like Snowflake, RDS/Postgres, DynamoDB.
AI/ML Experience: Exposure to the entire machine learning lifecycle, understanding of model development and inference.
Communication: Excellent documentation, presentation, and collaboration skills.
Nice to Have Experience with Cloud ML ecosystems such as AWS SageMaker, Azure ML, MLOps platforms like MLFlow, ModelOp, Seldon.
Familiarity with AWS and Azure AI services like Textract, Bedrock, Comprehend, Kendra, Cognitive Services.
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