Machine Learning Engineer

12+ years of overall IT development experience, with a strong background in backend and distributed systems.

7+ years of experience in Machine Learning, Data Engineering, or Applied AI engineering.

Strong proficiency in Python, with experience building modular, production-grade services.

Proven experience implementing Retrieval-Augmented Generation (RAG) and semantic search architectures.

Hands-on experience integrating and operationalizing OpenAI LLM APIs in production environments.

Solid experience deploying and managing systems within AWS environments, including services such as S3, Lambda, ECS/EKS, and IAM.

Experience building scalable, secure, and observable AI/ML systems in production.

Experience working with Amazon SageMaker and/or Amazon Bedrock for model development, deployment, or managed LLM services.

Strong familiarity with AWS data services, including AWS Glue, Amazon Athena, Amazon OpenSearch Service, and Amazon Aurora.

Hands-on experience designing and implementing ETL/ELT data pipelines in cloud environments.

Experience building LLM orchestration pipelines, including reasoning workflows, tool usage, and multi-step agent architectures.

Knowledge of LLM benchmarking, evaluation frameworks, and performance optimization (latency, cost, quality metrics).

Experience integrating enterprise systems using SnapLogic.

Exposure to Craxel Black Forest Time-Series Database (or similar time-series platforms); willingness to learn/train if not previously experienced.

Experience implementing Infrastructure as Code (IaC) using AWS CDK, CloudFormation, or Terraform.

Bachelor s degree in computer science or a related field.