Lead Machine Learning Engineer - Locals onlyTechTriad Inc • United States
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Lead Machine Learning Engineer - Locals only
TechTriad Inc
- United States
- United States
À propos
ML Engineering Lead
who thrives in early-stage, ambiguous environments. You’ve led ML systems from v1 to scale, and enjoy defining both the technical direction and the systems that power them. Your mission is to Own and lead the ML/AI function end-to-end, setting technical direction and standards across the company Architect and guide the development of multi-modal, agentic AI systems powering real-world workflows Define and oversee evaluation frameworks, datasets, and performance metrics to continuously improve agent quality Drive product ionization of ML systems, ensuring reliability, scalability, and compliance in real-world environments Build and mentor a high-performing ML team over time, setting best practices across modeling, experimentation, and deployment Who You Are 8+ years of experience in ML/AI engineering, including time as a technical lead or manager Proven track record of leading ML initiatives end-to-end, from problem definition → production deployment Deep experience with LLMs and/or agentic systems, ideally in real-world, customer-facing applications Strong understanding of ML fundamentals (deep learning, transformers, model evaluation, tradeoffs) Experience scaling ML systems in production, including monitoring, iteration, and reliability Demonstrated ability to lead engineers, influence architecture decisions, and drive technical direction Comfortable operating in early-stage, ambiguous environments with high ownership Strong communication skills with the ability to translate complex ML concepts into clear decisions Bonus Points If You Have experience building agentic systems, orchestration layers, or long-context reasoning systems Are comfortable across the stack (data → modelling → infra → APIs) Have worked with both open-source and closed LLMs, including fine-tuning or retrieval systems (RAG) Have a strong product mindset and care deeply about real-world impact, not just model performance
Compétences linguistiques
- English
Avis aux utilisateurs
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