AI/ML Engineer | $70-$200/hr Remote
Overview
At micro1, you’ll shape mission-critical government-focused ML initiatives while building our proprietary AI infrastructure. You’ll work with large language models, retrieval-augmented generation, and multi-agent systems to deliver secure, scalable machine learning solutions. Expect collaboration with cross-functional teams and exposure to frontier AI platforms and agentic tooling. Python, LLMs, RAG, and AWS power the work you’ll do daily.
What You'll Do7
- 1Architect and refine production-grade AI/ML models using LLMs, RAG, and careful prompt design.
- 2Set up and orchestrate multi-agent systems with frameworks like LangGraph and LangChain.
- 3Deploy and manage solutions in secure cloud environments such as AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
- 4Build data pipelines, run ETL processes, and maintain metadata catalogs and ontologies to ensure high-quality data for training and inference.
- 5Create and sustain REST APIs and SDK integrations to enable smooth data and model interactions.
- 6Collaborate with product, security, and engineering teams to follow secure coding and DevOps practices (CI/CD).
- 7Document technical decisions and explain complex concepts clearly to diverse stakeholders.
Requirements7
- 1Proficiency in Python for AI/ML development, including REST API and SDK integration experience.
- 2Hands-on work with LLMs, RAG systems, and prompt engineering in production contexts.
- 3Experience with multi-agent orchestration and tool frameworks such as LangGraph and LangChain.
- 4Deep knowledge of cloud AI services across AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
- 5Background in building and maintaining data pipelines, ontologies, metadata catalogs, and ETL processes.
- 6Strong understanding of secure coding practices and modern DevOps (CI/CD).
- 7Excellent written and verbal communication for effective collaboration and documentation.
Who Should Apply
The ideal candidate brings hands-on expertise with Python and AI tooling, including production-grade LLMs and RAG workflows, plus experience orchestrating multiple agents. The role may not be a fit for someone without exposure to regulated cloud environments or who lacks secure coding and CI/CD experience. Candidates often struggle if they can’t demonstrate end-to-end data pipelines or omit clear documentation. A track record of cross-functional collaboration and the ability to translate complex AI concepts for non-technical stakeholders strengthens candidacy.
Salary Insight
Pay ranges from 70 to 200 per hour; pay is discussed in later stages.
Location
Required Skills
Application Tip
Highlight hands-on projects showing production LLM deployment, RAG pipelines, and multi-agent orchestration using LangChain or LangGraph; quantify impact with metrics like latency, accuracy, or data processed per day.
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