Senior Director, Software Engineering – AI ML Engineering

Role Overview

We’re looking for a hands‑on technical leader to architect, fine‑tune, and deploy on‑device small language models (SLMs) for consumer security ’ll lead a focused team of 3–5 senior engineers while remaining deeply involved in the code and technical architecture. Your core responsibility is building high‑performance, privacy‑preserving AI models that run directly on user devices (Mac, iOS, Android, Linux). You’ll own model optimization, fine‑tuning for tool‑use accuracy, evaluation frameworks, and cost‑aware deployment strategies.

While you won’t own the agent orchestration platform itself, you’ll work closely with it to ensure models behave correctly in multi‑turn conversations and make reliable tool‑calling decisions. This role sits at the intersection of edge ML, applied LLMs, and production engineering. Success requires navigating real‑world tradeoffs: latency vs. capability, privacy vs. accuracy, on‑device vs. cloud execution, and cost vs. performance.

This is not a traditional director role. You’ll spend 60%+ of your time on technical architecture and implementation, with the remainder focused on mentoring senior engineers and setting technical direction.

• Design and deploy small language models optimized for on‑device inference (Mac, iOS, Android, Linux)
• Lead model optimization efforts including quantization, pruning, distillation, and efficient inference pipelines
• Fine‑tune models to improve tool selection accuracy and conversational behavior in security‑focused workflows
• Build evaluation frameworks to measure model efficacy, tool‑calling accuracy, conversation quality, and safety in production
• Create synthetic data and workflow simulations to train and validate security‑relevant conversations
• Partner closely with agent orchestration systems to optimize multi‑turn dialogue behavior and state handling
• Implement cost‑optimization strategies such as intelligent on‑device vs. cloud routing, prompt caching, batching, and token efficiency
• Integrate cloud‑based LLMs when deeper reasoning or broader context is required
• Build production ML systems that detect threats and protect users directly on‑device
• Set technical standards and architectural direction for AI/ML across the security platform
• Mentor principal engineers and architects while remaining hands‑on

• 10+ years of software engineering experience, with 5+ years focused on ML/AI
• Proven experience shipping ML models to production with transferable skills to deploy these on edge or mobile platforms
• Experience with conversational AI systems and tool/function‑calling architectures
• Strong Python and systems programming skills (C++ or Rust) for performance‑critical code
• Deep expertise in model optimization (INT4/INT8 quantization, pruning, distillation)
• Hands‑on experience with PyTorch and at least one edge deployment framework (Tensor Flow Lite, CoreML, ONNX Runtime, or llama.cpp)
• Experience building evaluation and benchmarking frameworks for ML systems
• Preferred:
  Experience applying ML systems in security, safety, or other adversarial domains
• Preferred:
  Master’s degree in CS, ML, or a related field (or equivalent practical experience)

• Pension and Retirement Plans
• Medical, Dental and Vision Coverage
• Paid Time Off
• Paid Parental Leave
• Support for Community Involvement

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