Head of Machine Learning

Stealth Startups

  • San Francisco, California
  • 5 days ago

    Highlights

    Collaborate closely with cross-functional teams (Product, Engineering, Research, Data Science) to identify high-impact opportunities for leveraging ML, define project scopes, and ensure successful integration of ML solutions. The ideal candidate will have a strong background in developing and deploying machine learning models at scale, a passion for driving technological advancement in AI, and a proven ability to manage and mentor high-performing teams.

    Numbers & Facts

    LocationSan Francisco, California

    Description

    Job brief

    Head of Machine Learning

    Minimum Years of Experience Required: 6+ Years

    Salary range: $220,000 - $250,000+

    Work Authorization: Candidates must be a Permanent Resident or already possess authorization to work in the United States. Please note, we are unable to sponsor work visas for this position.

    About the Role: We are seeking an experienced Head of Machine Learning to lead our innovative ML team. The ideal candidate will have a strong background in developing and deploying machine learning models at scale, a passion for driving technological advancement in AI, and a proven ability to manage and mentor high-performing teams. Join us to shape the future of AI in our products and services, focusing on cutting-edge research translation into production systems.

    Key Responsibilities:

    • Provide strategic direction and leadership for the Machine Learning department, aligning ML initiatives with overall company goals and product roadmaps.

    • Oversee the entire ML lifecycle, from research and experimentation to the design, development, deployment, and monitoring of robust and scalable ML models and algorithms in production environments.

    • Collaborate closely with cross-functional teams (Product, Engineering, Research, Data Science) to identify high-impact opportunities for leveraging ML, define project scopes, and ensure successful integration of ML solutions.

    • Drive the development and implementation of MLOps best practices to ensure model reliability, reproducibility, and efficient deployment.

    • Foster a culture of innovation, knowledge sharing, and continuous improvement within the ML team, staying abreast of the latest advancements in AI research and technology.

    • Manage team resources, including hiring, mentoring, and performance management, to build and retain a world-class ML organization.

    • Define and track key metrics for ML model performance, system health, and business impact.

    • Present ML strategies, progress, and results to executive leadership and external stakeholders.

    • Manage budgets and resource allocation for the Machine Learning function.

    Qualifications:

    • Minimum 6 years of professional experience in Machine Learning or a related field, with significant experience (typically 3+ years) in a leadership role managing ML teams.

    • Advanced degree (Master's or Ph.D.) in Computer Science, AI, Statistics, or a relevant quantitative discipline, with a strong foundation in ML theory and practice.

    • Proven track record of successfully leading complex ML projects from ideation through production deployment and impact measurement in a fast-paced environment.

    • Deep understanding of current ML techniques, including deep learning, reinforcement learning, and various model architectures, as well as experience with major ML frameworks (e.g., TensorFlow, PyTorch).

    • Experience with cloud platforms (AWS, Azure, GCP) and distributed computing for training and deploying large-scale ML models.

    • Strong knowledge of MLOps principles and tools for model versioning, training pipelines, deployment, monitoring, and explainability.

    • Excellent leadership, communication, and interpersonal skills, with the ability to inspire and guide technical teams and effectively communicate complex technical concepts to diverse audiences.

    • Experience with budgeting and resource allocation for ML initiatives.

    Benefits:

    • Flexible Work Arrangements (Hybrid/Remote options)

    • Comprehensive Health, Dental, and Vision Insurance

    • Stock Options or RSU program

    • Paid Parental Leave

    • 401(k) with company match

    • Unlimited or Generous Paid Time Off and Holidays

    • Professional Development Stipend for conferences, courses, and certifications

    • Wellness Programs and Mental Health Support

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