Head of AI/ML (Director/VP) - VC Backed Startups at Signalfire — Remote

## Join SignalFire’s Talent Network for Head of AI/ML (Director/VP) Roles at VC-Backed Startups

🛑 This is not an application for a specific job. Instead, this is a way to get on the radar of VC-backed startups that are actively hiring AI and machine learning leaders. If you have any questions, please direct inquiries to talentnetwork@signalfire.com.

We’re looking to connect with exceptional Heads of AI/ML, including Director- and VP-level leaders, who are excited about defining AI strategy, building high-performing teams, and translating emerging technologies into differentiated products and business outcomes.

## Who Should Join?

We’re looking for leaders who are:

✔ Passionate about building AI-native products and applying machine learning to meaningful customer problems ✔ Experienced in defining AI/ML strategy and leading teams from research and experimentation through production deployment ✔ Excited to partner with founders, product leaders, and engineering teams to shape company and product direction ✔ Comfortable balancing technical depth, organizational leadership, and commercial impact

## Typical Roles & Responsibilities

• Define and execute the company’s AI and machine learning strategy in alignment with product and business priorities
• Build, lead, and develop high-performing teams across machine learning, applied AI, data science, and research
• Identify high-impact opportunities to apply AI and translate them into differentiated product capabilities
• Lead the development, evaluation, deployment, and continuous improvement of production ML systems
• Establish technical standards for model quality, experimentation, reliability, observability, and responsible AI
• Guide decisions across 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 required to improve model performance
• Evaluate emerging models, research, and tooling while maintaining a practical focus on customer and business value
• Communicate AI strategy, capabilities, limitations, and investment priorities to executive teams, boards, customers, and partners
• Support recruiting, organizational design, and workforce planning for the company’s AI and ML functions
• Help establish safeguards around privacy, security, bias, explainability, and regulatory requirements

## Common Qualifications

While each startup has its own hiring criteria, many Head of AI/ML roles in our network look for:

• 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 closely with product, engineering, data, and go-to-market leaders
• Strong judgment around model quality, latency, cost, scalability, safety, and reliability
• Ability to operate effectively 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

## 💡 Technologies You Might Work With:

• Languages & Frameworks: Python, PyTorch, TensorFlow, JAX, scikit-learn, Hugging Face
• Generative AI: Large language models, multimodal models, retrieval-augmented generation, fine-tuning, prompt engineering, agentic systems
• Data & Infrastructure: Spark, Databricks, Snowflake, Kafka, Airflow, vector databases, feature stores
• Cloud & MLOps: AWS, GCP, Azure, Kubernetes, Docker, MLflow, Weights & Biases, SageMaker, Vertex AI
• Models & Platforms: OpenAI, Anthropic, Google, Meta, open-source foundation models, proprietary model architectures

## What Happens Next?

• Submit your application to join SignalFire’s Talent Ecosystem.
• We review applications on an ongoing basis to identify strong candidates.
• If there’s a match, a SignalFire talent partner or a leader from one of our startups may reach out directly.
• No match yet? We’ll keep your profile on file for future AI and machine learning leadership roles across our portfolio.