• Director, AI Engineering

    BeOne Medicines (Emeryville, CA)


    The Director AI Engineering will lead and manage a team of AI and machine learning engineers dedicated to building, deploying, and optimizing AI-driven solutions across various applications. This role is pivotal for executing the AI strategy, managing the end-to-end development lifecycle of AI models, ensuring the creation of robust and scalable solutions, and fostering a data-driven culture within the organization.

     

    + Lead the technical design, development, and deployment of AI/ML solutions, ensuring they align with project goals and business objectives.

    + Collaborate closely with data scientists, product managers, software engineers, and other stakeholders to effectively integrate AI models into production systems and business workflows.

    + Contribute significantly to architectural decisions for AI infrastructure, with a focus on scalability, reliability, and efficient model lifecycle management (MLOps).

    + Manage, mentor, and develop a team of AI engineers, establishing and promoting best practices in model development, rigorous testing, deployment, and ongoing maintenance.

    + Oversee the implementation and execution of comprehensive testing, monitoring, and validation processes for AI models to ensure high standards of accuracy, performance, and reliability.

    + Stay current with industry advancements and emerging technologies in AI and machine learning, evaluating and recommending new tools, frameworks, and techniques to enhance the team's capabilities and efficiency.

    + Foster a collaborative, innovative, and continuous learning environment within the AI engineering team, supporting the career development and technical growth of team members.

    + Manage the operational aspects of AI solutions, including their integration with data storage systems, cloud platforms, and data engineering pipelines to support high-performance and scalable applications.

    + Ensure all AI-driven solutions are developed and deployed in compliance with data governance policies, privacy regulations, security standards, and ethical considerations.

    + Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a closely related technical field. (A Ph.D. is a plus).

    + 10+ years of progressive experience in AI/ML engineering, with at least 5+ years in a leadership or management capacity, directly managing engineering teams or significant AI/ML projects.

    + Strong, hands-on background in AI/ML model development, deployment, and lifecycle management, utilizing common frameworks such as TensorFlow, PyTorch, or Scikit-Learn.

    + Demonstrated experience with prompting engineering, retrieval-augmented generation (RAG), model fine-tuning, and other relevant advanced AI techniques.

    + Proficiency with data processing technologies, various database systems (relational and NoSQL), and cloud computing platforms (e.g., AWS, Azure, GCP).

    + Solid experience with MLOps practices and tools, including CI/CD pipelines for machine learning, model versioning, automated testing, and monitoring.

    + Excellent communication, interpersonal, and leadership skills, with a proven ability to lead technical teams, collaborate effectively across functions, and articulate complex technical concepts to diverse audiences.

    + A strong track record of successfully delivering impactful and scalable AI/ML solutions into production.

    + Good understanding of agile development methodologies and familiarity with project management tools (e.g., Jira, Asana).

    + Knowledge of data privacy, security best practices, and ethical considerations pertinent to AI development and deployment.

    + Preferred Skills:

    + Solid experience with deep learning architectures (e.g., CNNs, RNNs, Transformers), reinforcement learning, or generative AI models.

    + Familiarity with AI research methodologies.

    + Proven ability to scale AI/ML systems and infrastructure effectively in a production environment.

     

    All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.