M

Forward Deployed Engineer (AI/ML Infrastructure & Partner Development)

micro1 • Brazil
Full Remote
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Seeking a Mid-Senior level **Forward Deployed Engineer** to bridge AI research and enterprise partnerships. Focus on building ML pipelines, agentic systems, and data intelligence frameworks for production deployment. Requires Python expertise, LLM/agent system experience, and strong partner-facing technical ownership.

Key Highlights
Remote role with travel requirements
Base salary range: $180,000–$250,000 USD with equity and bonuses
Focus on AI research partnerships, ML infrastructure, and agentic systems
Key Responsibilities
Define research goals and technical requirements for AI lab/enterprise partnerships
Build large-scale data intelligence systems for data collection, organization, and evaluation
Implement ML pipelines for data curation, model training, evaluation, and deployment
Design data taxonomies, labeling systems, and quality frameworks
Develop LLM applications (multi-agent systems, RAG workflows, evaluation harnesses)
Partner with research/engineering teams to translate AI problems into production systems
Develop infrastructure for model inference, experimentation, and deployment
Technical Skills Required
Python (production systems) Machine Learning LLM/Agentic Systems
Benefits & Perks
Up to 100% health-insurance premium reimbursement
401(K) plan with company match
Performance-based bonuses
Equity compensation
Nice to Have
Experience at startups or AI infrastructure companies
Background in multi-turn agent evaluation or workflow automation
Technical partnership experience with external customers/research teams
Familiarity with modern LLM tooling and agent frameworks

Job Description

The Role

We’re hiring a Forward Deployed Engineer to work directly with the world’s leading AI labs and enterprises as a technical research and implementation partner. This role sits at the intersection of applied AI, ML infrastructure, data intelligence, and partner-facing product development.

You’ll help strategic partners define research directions, structure and curate high-quality data, implement ML and evaluation pipelines, and build the agentic systems that extend multi-turn agents and workflows in production. You should be comfortable moving between ambiguous research questions, technical architecture, hands-on engineering, and partner-facing execution.

What You’ll Work On

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