LeadershipFull-timeHybrid

Director of AI & Machine Learning

Lead APPIT Software's AI and machine learning strategy from San Francisco, building intelligent products that leverage LLMs, predictive analytics, and computer vision to solve complex enterprise challenges.

San Francisco, USA

Full-time

Leadership

Responsibilities

Define and own the AI/ML product strategy, identifying high-impact opportunities to embed intelligence across APPIT's product suite including lead scoring, anomaly detection, and workflow automation
Build and lead a world-class AI/ML team of 15-25 researchers and engineers, establishing a culture of innovation, rigorous experimentation, and responsible AI practices
Architect scalable ML infrastructure including model training pipelines, feature stores, experiment tracking, and real-time inference systems handling millions of predictions daily
Drive applied research in LLM fine-tuning, retrieval-augmented generation, and agentic AI systems to create differentiated enterprise solutions
Establish partnerships with academic institutions, open-source communities, and cloud AI platform providers to accelerate innovation velocity
Present AI strategy and results to the executive team and board, translating complex technical capabilities into clear business value narratives with ROI metrics

Requirements

12+ years of experience in machine learning and AI with at least 4 years in Director or Head of AI roles at technology companies
Publication record in top-tier venues (NeurIPS, ICML, ACL, CVPR) or equivalent industry research impact with deployed ML systems at scale
Deep expertise in modern ML stack: PyTorch, transformer architectures, distributed training, MLOps platforms (MLflow, Kubeflow, SageMaker)
Proven experience deploying production ML systems handling high-throughput, low-latency inference with robust monitoring and drift detection
Strong understanding of LLM ecosystems including fine-tuning, prompt engineering, RAG architectures, and emerging agentic frameworks
Exceptional ability to communicate complex AI concepts to non-technical stakeholders and align AI initiatives with business priorities

Nice to Have

PhD in Computer Science, Machine Learning, Statistics, or related quantitative field
Experience building AI products in CRM, marketing analytics, or enterprise SaaS domains
Contributions to open-source ML frameworks or published patents in AI/ML technologies

Skills

Machine LearningDeep LearningLLM/GenAIMLOpsPythonTeam LeadershipStrategic VisionResearch Management

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Director of AI & Machine Learning

San Francisco, USA

Full-time

Leadership

Responsibilities

Define and own the AI/ML product strategy, identifying high-impact opportunities to embed intelligence across APPIT's product suite including lead scoring, anomaly detection, and workflow automation
Build and lead a world-class AI/ML team of 15-25 researchers and engineers, establishing a culture of innovation, rigorous experimentation, and responsible AI practices
Architect scalable ML infrastructure including model training pipelines, feature stores, experiment tracking, and real-time inference systems handling millions of predictions daily
Drive applied research in LLM fine-tuning, retrieval-augmented generation, and agentic AI systems to create differentiated enterprise solutions
Establish partnerships with academic institutions, open-source communities, and cloud AI platform providers to accelerate innovation velocity
Present AI strategy and results to the executive team and board, translating complex technical capabilities into clear business value narratives with ROI metrics

Requirements

12+ years of experience in machine learning and AI with at least 4 years in Director or Head of AI roles at technology companies
Publication record in top-tier venues (NeurIPS, ICML, ACL, CVPR) or equivalent industry research impact with deployed ML systems at scale
Deep expertise in modern ML stack: PyTorch, transformer architectures, distributed training, MLOps platforms (MLflow, Kubeflow, SageMaker)
Proven experience deploying production ML systems handling high-throughput, low-latency inference with robust monitoring and drift detection
Strong understanding of LLM ecosystems including fine-tuning, prompt engineering, RAG architectures, and emerging agentic frameworks
Exceptional ability to communicate complex AI concepts to non-technical stakeholders and align AI initiatives with business priorities

Nice to Have

PhD in Computer Science, Machine Learning, Statistics, or related quantitative field
Experience building AI products in CRM, marketing analytics, or enterprise SaaS domains
Contributions to open-source ML frameworks or published patents in AI/ML technologies

Skills

Machine LearningDeep LearningLLM/GenAIMLOpsPythonTeam LeadershipStrategic VisionResearch Management

Director of AI & Machine Learning

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Requirements

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Skills

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