Head of AI/ML – VC Backed Startups

SignalFire

AI/ML executive defining strategy, building leadership teams, and deploying production systems for SignalFire’s VC-backed startup portfolio. Translating emerging technologies into differentiated products and business outcomes.

Posted 8/5/2026full-time🇺🇸 United StatesLead💰 $250,000 - $300,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in defining and executing AI and machine learning strategies, leading high-performing teams, and developing production ML systems. Proficient in integrating AI capabilities into scalable products while ensuring model quality, reliability, and compliance with regulatory standards.

Highest-signal resume keywords

Machine Learning StrategyTeam LeadershipProduction ML Systems DevelopmentLarge Language ModelsTechnical Judgment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningArtificial IntelligenceData ScienceModel EvaluationData PipelinesDeep LearningGenerative AIModel Fine-TuningStatistical AnalysisSoftware Engineering

Soft Skills

CommunicationJudgmentCollaborationStrategic ThinkingTeam Management

Tools & Technologies

PythonPyTorchTensorFlowJAXScikit-learnAWSGCPAzureKubernetesDocker

Certifications & Qualifications

Advanced Degree in Computer ScienceAdvanced Degree in Machine LearningAdvanced Degree in StatisticsAdvanced Degree in Mathematics

Industry Keywords

AI CapabilitiesModel QualityResponsible AIData GovernanceCustomer OutcomesHigh-Growth TechnologyStartup EnvironmentProduct DifferentiationRegulatory RequirementsOpen-Source Foundation Models

Tech Stack

Tools & technologies

AirflowAWSAzureDockerGoogle Cloud PlatformKafkaKubernetesPythonPyTorchScikit-LearnSparkTensorflow

About the role

Key responsibilities & impact

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
Submit an application to join SignalFire’s Talent Ecosystem
Work with SignalFire talent partners or leaders from portfolio startups if a match is identified

Requirements

What you’ll need

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
Experience with technologies including Python, PyTorch, TensorFlow, 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, SageMaker, Vertex AI, OpenAI, Anthropic, Google, Meta, open-source foundation models, and proprietary model architectures

Benefits

Comp & perks

$250K – $300K base compensation
Equity offered