Head of AI Engineering

About CompScience

At CompScience, we're not just building software—we're saving lives. We're a high-growth startup on a mission to prevent 1 million workplace injuries through bold technological innovations, ensuring that everyone can go home safe at the end of the day.

Founded in 2019 and backed by investors from SpaceX, Tesla, and Anduril, we've assembled a powerhouse team that bridges two worlds:

• Cutting-Edge Technology: Our engineering team is comprised of distinguished computer vision engineers, software architects, and data scientists from the self-driving car industry. They bring unparalleled expertise in AI and machine learning to the realm of workplace safety.

• Insurance Acumen: Our insurance team comprises seasoned professionals who understand the nuances of workers' compensation policies. They work hand-in-hand with our tech experts to translate advanced analytics into tangible insurance products that truly serve our clients' needs.

Our groundbreaking perception-based risk assessment program, the first of its kind, provides the most comprehensive data stream available for risk analysis and monitoring and has proven to significantly reduce accidents in some of the world's most hazardous occupations.

About the Role

We are looking for an Head of AI Engineering to research and deploy new systems for generating deep contextual insights from video data. The causal risk factors that you develop will prevent millions of people from getting hurt or killed on the job.  This is a hands-on position requiring the ability to design, develop, and implement solutions individually while building a team.

Responsibilities

• Proven leadership in defining and executing a comprehensive AI strategy, including roadmap development and successful integration of AI solutions into core product offerings.

• Extensive experience architecting and developing compound AI systems, specifically combining Computer Vision (CNNs) and Large Language Models (LLMs) to extract insights from both structured and unstructured data sources.

• Deep expertise in AI model design, training, and optimization, including hands-on experience with real-time video analysis using CNNs and fine-tuning LLMs for domain-specific applications (e.g., safety intelligence, risk assessment).

• Demonstrated ability to design and deploy scalable AI architectures across diverse environments, including on-premise, edge devices, and cloud platforms, with a strong understanding of MLOps principles and practices.

• Experience building and leading MLOps & AI Infrastructure, building pipelines, implementing AI model monitoring, and integrating continuous learning to improve AI accuracy and efficiency.

• Strong track record of cross-functional collaboration, with proven ability to work effectively with engineering, product, and data science teams to deliver AI-driven solutions, while ensuring compliance with relevant regulatory and ethical AI standards.

Required Experience

• PhD or MS in AI, Computer Vision, Machine Learning, or a related field, coupled with 8+ years of industry experience in AI/ML, including a strong background in both Convolutional Neural Networks (CNNs) and Large Language Models (LLMs).

• Proven expertise in computer vision models (e.g., YOLO, EfficientNet, etc.) and LLMs (e.g., GPT, LLaMA, Claude, Gemini), including experience with fine-tuning techniques for both.

• Strong programming skills in Python and hands-on experience with deep learning frameworks (PyTorch, TensorFlow) and libraries (Hugging Face Transformers).

• Hands-on experience in developing and deploying multi-modal AI systems that integrate text, vision, and structured data (at work or at home). Knowledge of edge AI techniques, real-time inference, and low-latency model optimization.

Nice-to-have

• Demonstrated experience in AI safety, risk assessment, or workplace automation, with a strong understanding of relevant regulatory frameworks (e.g., OSHA) and compliance considerations for AI in workplace settings.

• Proven experience fine tuning Large Language Models (LLMs) with external data sources, utilizing techniques such as Retrieval-Augmented Generation (RAG), embeddings, and retrieval models to enhance LLM capabilities.

• Familiarity with Explainable AI (XAI) techniques and their application in developing transparent and trustworthy AI systems, particularly in high-stakes environments.

Working at CompScience

Compensation

CompScience is committed to fair and equitable compensation practices. The annual salary range for this role is $185,000 – $300,000. Compensation is determined within the range based on your qualifications and experience. Our total compensation package also includes equity and comprehensive benefits.

Benefits at CompScience

• Remote-first work environment with regional hubs

• Fast-paced startup environment where your ideas can quickly become reality

• Opportunity to wear multiple hats and grow beyond your job description

• Remote-first culture with home office support

• Comprehensive health benefits (Medical, Dental, Vision, HSA)

• 401(k) plan and life insurance

• Flexible time off and 12 weeks parental leave

• Professional development reimbursement

Our Ideal Teammate:

• Thrives in a fast-paced startup and is comfortable navigating ambiguity

• Excited to wear multiple hats and grow rapidly

• Committed to our mission of saving lives through technology