Head of Machine Learning

Head of Machine Learning

Clarivos LLC – Seattle, WA (Remote, US Based). Full‑time, Senior level.

Reports to:

Sr VP AI Platform, Interim CTO. Department:
GenAI Modeling. FLSA Category:
Exempt. Travel Requirement: 0‑10% quarterly for meetings.

As Head of Machine Learning, you will own and lead the company’s end‑to‑end ML and GenAI strategy. This senior technical leadership role has hands‑on architectural responsibility and partners closely with Product, Engineering, and Data teams to deliver production‑grade AI systems that power our core Mar Tech and AdTech capabilities.

• Define and own the ML and GenAI roadmap, aligned with product, business, and platform strategy.
• Establish architectural standards for LLMs/SLMs, agentic systems, real‑time inference, and feedback‑driven learning loops.
• Drive the transition toward a fully AI‑native, agent‑powered platform.

• Architect and oversee scalable LLM/GenAI systems for Mar Tech/AdTech use cases, including:
  • Content generation and optimization
  • Sentiment and resonance analysis
  • Strategy recommendation and campaign optimization
  • Audience segmentation, targeting, and personalization
• Design and deploy multi‑agent systems using frameworks such as Lang Graph, Auto Gen, CrewAI, MCP, or equivalent.
• Own end‑to‑end ML system design: data ingestion, feature pipelines, training, inference, evaluation, and monitoring.
• Lead decisions around foundation models, fine‑tuning strategies, RAG pipelines, embeddings, and ranking systems.

• Establish best practices for LLMOps / MLOps, including:
  • Model evaluation, A/B testing, and continuous learning
  • Monitoring, drift detection, and reliability at scale
  • Safe and explainable AI practices
• Oversee scalable training and inference infrastructure, including multi‑GPU environments (A100/H100‑class systems).
• Ensure ML systems meet performance, cost, and latency requirements for real‑time production use.

• Build, mentor, manage, and scale a high‑performing ML organization across senior, principal, and junior talent.
• Set technical bar, review standards, and guardrails to ensure quality and sustainability in an AI‑augmented development environment.
• Partner with Engineering leadership to balance velocity, code quality, and long‑term maintainability.

• Work closely with Product, Data, and Platform teams to translate business needs into scalable ML capabilities.
• Communicate complex ML concepts clearly to executive leadership, stakeholders, and the Board.
• Contribute to technical narratives used for fundraising, company valuation, and strategic planning.

• 8–12+ years of experience in ML/AI roles, including senior or principal‑level ownership of production ML systems.
• 3+ years of hands‑on experience building with LLMs/SLMs in real‑world applications.
• PhD degree in Computer Science, Engineering, or related field.
• Deep expertise in Deep Learning and NLP (PyTorch preferred; Tensor Flow acceptable).
• Proven experience fine‑tuning and deploying foundation models (LLaMA, Mistral, GPT‑style models).
• Strong command of Hugging Face ecosystem and fine‑tuning techniques (LoRA, PEFT, adapters).
• Experience with vector search and retrieval systems (FAISS, PGVector, Pinecone, Redis Vector).
• Familiarity with agent‑based and reasoning frameworks (Lang Graph, ReAct, Auto Gen, CrewAI, MCP, etc.).
• Experience with ML experimentation and observability tools (MLflow, Weights & Biases, Prompt Layer, etc.).
• Strong background in cloud‑native ML systems (AWS, GCP, or Azure).
• Solid understanding of distributed systems, GPU optimization, batching, and cost‑aware inference.
• Excellent software engineering fundamentals (Python, APIs, microservices, Docker, Kubernetes).