Head of AI​/ML – VC Backed Startups

• Define and execute company AI and machine learning strategy aligned with product and business priorities
• Build, lead, and develop teams across machine learning, applied AI, data science, and research
• Identify high-impact AI opportunities and translate them into differentiated product capabilities
• Lead development, evaluation, deployment, and continuous improvement of production ML systems
• Establish technical standards for model quality, experimentation, reliability, observability, and responsible AI
• Guide decisions on model selection, fine-tuning, retrieval, data strategy, infrastructure, and build-versus-buy tradeoffs
• Partner with engineering and product leaders to integrate AI capabilities into scalable customer-facing products
• Oversee data collection, labeling, governance, and feedback loops
• Evaluate emerging models, research, and tooling with focus on customer and business value
• Communicate AI strategy, capabilities, limitations, and investment priorities to executives, boards, customers, and partners
• Support recruiting, organizational design, and workforce planning for AI and ML functions
• Establish safeguards for privacy, security, bias, explainability, and regulatory requirements
• Maintain profile consideration for future AI and machine learning leadership roles across the portfolio

• 10+ years of experience across machine learning, artificial intelligence, data science, or software engineering, including meaningful leadership experience
• Proven experience building and scaling AI/ML teams in startup or high-growth technology environments
• Track record of developing and deploying machine learning systems into production
• Strong technical foundation across modern ML methods, model evaluation, data pipelines, and production infrastructure
• Experience applying large language models, generative AI, deep learning, or traditional machine learning to real-world products
• Ability to connect technical investments to product differentiation, customer outcomes, and business value
• Experience partnering with product, engineering, data, and go-to-market leaders
• Strong judgment around model quality, latency, cost, scalability, safety, and reliability
• Ability to operate across hands-on technical leadership, team management, and executive-level strategy
• Advanced degree in computer science, machine learning, statistics, mathematics, or a related field may be preferred but is not always required
• Experience with technologies including Python, PyTorch, Tensor Flow, JAX, scikit-learn, Hugging Face, large language models, multimodal models, retrieval-augmented generation, fine-tuning, prompt engineering, agentic systems, Spark, Databricks, Snowflake, Kafka, Airflow, vector databases, feature stores, AWS, GCP, Azure, Kubernetes, Docker, MLflow, Weights & Biases, Sage Maker, Vertex AI, and major model platforms

Demonstrates expertise in defining and executing AI and machine learning strategies, leading teams in developing scalable ML systems, and ensuring model quality and compliance with privacy and regulatory standards. Proven ability to connect technical investments to business value and product differentiation.

• Machine Learning Strategy
• Team Leadership in AI/ML
• Model Evaluation and Deployment
• Large Language Models Experience
• Technical Leadership and Strategy

• Machine Learning
• Artificial Intelligence
• Data Science
• Model Evaluation
• Data Pipelines
• Deep Learning
• Generative AI
• Statistical Analysis
• Software Engineering
• Technical Standards

• Judgment
• Communication
• Collaboration
• Organizational Design
• Team Management

• Advanced Degree in Computer Science
• Advanced Degree in Machine Learning
• Advanced Degree in Statistics
• Advanced Degree in Mathematics

• AI Opportunities
• Product Capabilities
• Production ML Systems
• Data Governance
• Responsible AI
• Customer Outcomes
• Business Value
• Startup Environment
• High-Growth Technology
• Model Platforms

• Python
• Py Torch
• Tensor Flow
• JAX
• Scikit-learn
• AWS
• GCP
• Azure
• Kubernetes
• Docker