Senior ML Engineer (GenAI, AWS)

TL;DR

Senior ML Engineer (GenAI, AWS): Designing and implementing end-to-end ML solutions from experimentation to production with an accent on GenAI, RAG systems, and scalable ML infrastructure. Focus on optimizing model performance, building robust LLM-based applications, and implementing MLOps pipelines on AWS.

Location: Fully remote (Colombia)

Company

AI consulting firm specializing in building ML infrastructure to drive end-to-end AI transformations across various industries including Healthcare, Retail, and Manufacturing.

What you will do

• Design and implement end-to-end ML solutions and scalable infrastructure from experimentation to production.
• Build production-ready LLM applications using RAG architectures and vector databases.
• Optimize model performance, efficiency, and reliability while writing maintainable production-quality code.
• Mentor junior and mid-level ML engineers and conduct rigorous code reviews.
• Collaborate with cross-functional teams (DevOps, Data Engineering, SAs) to develop reusable ML accelerators.
• Stay current with ML research and propose improvements to existing architectural decisions.

Requirements

• Advanced proficiency in Python, SQL, and data processing libraries (pandas, numpy).
• Strong experience with ML frameworks (PyTorch, TensorFlow) and Deep Learning (Transformers, CNNs, RNNs).
• Proven experience building production LLM applications, including prompt engineering and RAG systems.
• Expertise in AWS ML services (SageMaker, Lambda) and containerization (Docker).
• Practical knowledge of MLOps tools (MLflow, Weights and Biases) and CI/CD pipelines.
• Experience with distributed computing (Spark) and Infrastructure as Code (Terraform).

Nice to have

• Experience with taxonomies or ontologies.
• Practical experience with Dask or Great Expectations.
• Experience orchestrating complicated ML pipelines.

Culture & Benefits

• Long-term B2B collaboration.
• Fully remote work setup.
• Budget for medical insurance.
• Paid sick leave, vacation, and public holidays.
• Continuous learning support with unlimited AWS certification sponsorship.

Hiring process

• Recruitment Interview.
• Technical Interview.
• HR Interview.
• Hiring Manager Interview.