SharkNinja is looking to define and own the ML/AI strategy aligned with enterprise objectives, balancing near-term value and long-term scalability. Partner with AI Product Management on roadmap prioritization and resource allocation. Serve as executive advisor on AI/ML trends, vendor landscape, and technology adoption.
Requirements
- 7+ years in applied machine learning and AI leadership roles.
- Proven record delivering enterprise-scale ML solutions tied to measurable outcomes.
- Deep expertise in ML engineering, data science, and MLOps.
- Hands-on experience with cloud AI/ML stacks (AWS, Azure, GCP), modern data platforms (Snowflake, dbt), and vector search/RAG.
- Demonstrated ability to lead build vs. buy evaluations and present recommendations to executives.
- Experience in consumer goods, retail, or eCommerce optimization (e.g., Amazon marketplace, ad spend optimization).
- Exposure to LLMOps frameworks, guardrail tooling, and prompt engineering.
Responsibilities
- Lead development of production-grade ML systems (predictive models, recommendation engines, generative AI apps).
- Build reusable components (feature stores, vector databases, evaluation frameworks).
- Ensure models meet KPIs for accuracy, latency, cost, and business impact.
- Directly manage the allocation of Capex funds to maximize ROI in platforms, tooling, and engineering capacity.
- Establish enterprise MLOps practices (CI/CD, automated testing, monitoring, retraining).
- Define standards for data quality, model observability, prompt/version management, and reproducibility.
- Partner with Security, Legal, and Data Governance to enforce safety, privacy, and compliance.
Other
- The Director builds and manages high-performing ML engineering and MLOps teams, sets standards for responsible AI, and ensures SharkNinja’s AI platforms are secure, reliable, and cost-effective.
- The role is also accountable for leveraging Capex investments to deliver high-return AI capabilities and for managing key partnerships and vendor relationships to accelerate delivery.
- Partner with AI Product Management on roadmap prioritization and resource allocation.
- Serve as executive advisor on AI/ML trends, vendor landscape, and technology adoption.
- Strong executive communication and stakeholder leadership.
