Head of AIML (DirectorVP) 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 .

At SignalFire we partner with top early-stage startups that are shaping the future of technology. Our portfolio spans 200 innovative companies across AI cybersecurity healthtech fintech developer tools and enterprise SaaS.

Were 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.

By joining SignalFires Talent Network your profile will be shared with our portfolio companies giving you visibility into exclusive early-stage opportunities that may not be publicly listed.

Were 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

• Define and execute the companys 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 companys AI and ML functions

• Help establish safeguards around privacy security bias explainability and regulatory requirements

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

• 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

1. Submit your application to join SignalFires Talent Ecosystem.

2. We review applications on an ongoing basis to identify strong candidates.

3. If theres a match a SignalFire talent partner or a leader from one of our startups may reach out directly.

4. No match yet Well keep your profile on file for future AI and machine learning leadership roles across our portfolio.

Required Experience:

Exec