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The Senior Technical Project Manager will oversee new product development in the Frozen Treats category, leading cross-functional teams from concept to production, managing budgets, schedules, and risk communication with stakeholders.
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Beauty • Robotics • Design • Appliances • Manufacturing
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Beauty • Robotics • Design • Appliances • Manufacturing
The Senior Product Safety & Compliance Engineer will manage certification projects for medical devices, ensuring compliance with regulatory requirements, performing risk analysis, and mentoring junior staff.
Top Skills:
Fda 510(K)Iec 60601-1Iec 60601-1-11Iec 62304Iec 62366-1Iso 10993Iso 13485Iso 14971
About Us
SharkNinja is a global product design and technology company, with a diversified portfolio of 5-star rated lifestyle solutions that positively impact people's lives in homes around the world. Powered by two trusted, global brands, Shark and Ninja, the company has a proven track record of bringing disruptive innovation to market, and developing one consumer product after another has allowed SharkNinja to enter multiple product categories, driving significant growth and market share gains. Headquartered in Needham, Massachusetts with more than 3,600+ associates, the company's products are sold at key retailers, online and offline, and through distributors around the world.
Position Summary
The Director of ML and AI leads SharkNinja's enterprise-wide machine learning strategy, delivery, and operations. This role partners with the AI Product Manager to translate business priorities into scalable AI systems that deliver measurable business impact. 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.
Key Responsibilities
Strategy &Vision - 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.
ML Engineering & Delivery- 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.
ML Ops &Platform Standards - 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.
Build vs. Buy Lead technical due diligence and financial modeling for AI/ML investments. Collaborate with Product Management on vendor evaluations and build vs. buy decisions. Publish decision logs with risks and contingency plans.
Cross-Functional Integration- Partner with Platform, Data Engineering, and Enterprise MDM to ensure AI solutions are built on trusted, standardized data. Lead technical design for API-first and event-driven integrations across ERP, CRM, and eCommerce systems.
Partners &Vendors- Own relationships with key AI/ML technology vendors and service providers. Negotiate contracts, SLAs, and deliverables. Run proofs of value and ensure third-party contributions meet enterprise standards. Build strategic alliances with cloud providers, model vendors, and consultancies to accelerate delivery.
Talent & Culture - Recruit, mentor, and retain ML engineers, data scientists, and MLOps specialists. Foster a culture of experimentation, transparency, and measurable impact.
Required Qualifications• 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.• Strong executive communication and stakeholder leadership.
Preferred Qualifications• Experience in consumer goods, retail, or eCommerce optimization (e.g., Amazon marketplace, ad spend optimization).• Experience with Salesforce Cloud suite and customer data platforms.• Exposure to LLMOps frameworks, guardrail tooling, and prompt engineering.• Familiarity with regulatory compliance and data privacy in AI systems.
Our Culture
At SharkNinja, we don't just raise the bar-we push past it every single day. Our Outrageously Extraordinary mindset drives us to tackle the impossible, push boundaries, and deliver results that others only dream of. If you thrive on breaking out of your swim lane, you'll be right at home.
What We Offer
We offer competitive health insurance, retirement plans, paid time off, employee stock purchase options, wellness programs, SharkNinja product discounts, and more. We empower your personal and professional growth with high impact Learning Programs featuring bold voices redefining what's possible. When you join, you're not just part of a company-you're part of an outrageously extraordinary community. Together, we won't just launch products-we'll disrupt entire markets.
At SharkNinja, Diversity, Equity, and Inclusion are vital to our global success. Valuing each unique voice and blending all of our diverse skills strengthens SharkNinja's innovation every day. We support ALL associates in bringing their authentic selves to work, making an impact, and having the opportunity for career acceleration. With help from our leadership, associates, and our community, we aim to have equity be a key component of the SharkNinja DNA.
Learn more about us:
Life At SharkNinja
Outrageously Extraordinary
SharkNinja Candidate Privacy Notice
We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, disability, or any other class protected by legislation, and local law. SharkNinja will consider reasonable accommodations consistent with legislation, and local law. If you require a reasonable accommodation to participate in the job application or interview process, please contact SharkNinja People & Culture at [email protected]
SharkNinja is a global product design and technology company, with a diversified portfolio of 5-star rated lifestyle solutions that positively impact people's lives in homes around the world. Powered by two trusted, global brands, Shark and Ninja, the company has a proven track record of bringing disruptive innovation to market, and developing one consumer product after another has allowed SharkNinja to enter multiple product categories, driving significant growth and market share gains. Headquartered in Needham, Massachusetts with more than 3,600+ associates, the company's products are sold at key retailers, online and offline, and through distributors around the world.
Position Summary
The Director of ML and AI leads SharkNinja's enterprise-wide machine learning strategy, delivery, and operations. This role partners with the AI Product Manager to translate business priorities into scalable AI systems that deliver measurable business impact. 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.
Key Responsibilities
Strategy &Vision - 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.
ML Engineering & Delivery- 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.
ML Ops &Platform Standards - 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.
Build vs. Buy Lead technical due diligence and financial modeling for AI/ML investments. Collaborate with Product Management on vendor evaluations and build vs. buy decisions. Publish decision logs with risks and contingency plans.
Cross-Functional Integration- Partner with Platform, Data Engineering, and Enterprise MDM to ensure AI solutions are built on trusted, standardized data. Lead technical design for API-first and event-driven integrations across ERP, CRM, and eCommerce systems.
Partners &Vendors- Own relationships with key AI/ML technology vendors and service providers. Negotiate contracts, SLAs, and deliverables. Run proofs of value and ensure third-party contributions meet enterprise standards. Build strategic alliances with cloud providers, model vendors, and consultancies to accelerate delivery.
Talent & Culture - Recruit, mentor, and retain ML engineers, data scientists, and MLOps specialists. Foster a culture of experimentation, transparency, and measurable impact.
Required Qualifications• 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.• Strong executive communication and stakeholder leadership.
Preferred Qualifications• Experience in consumer goods, retail, or eCommerce optimization (e.g., Amazon marketplace, ad spend optimization).• Experience with Salesforce Cloud suite and customer data platforms.• Exposure to LLMOps frameworks, guardrail tooling, and prompt engineering.• Familiarity with regulatory compliance and data privacy in AI systems.
Our Culture
At SharkNinja, we don't just raise the bar-we push past it every single day. Our Outrageously Extraordinary mindset drives us to tackle the impossible, push boundaries, and deliver results that others only dream of. If you thrive on breaking out of your swim lane, you'll be right at home.
What We Offer
We offer competitive health insurance, retirement plans, paid time off, employee stock purchase options, wellness programs, SharkNinja product discounts, and more. We empower your personal and professional growth with high impact Learning Programs featuring bold voices redefining what's possible. When you join, you're not just part of a company-you're part of an outrageously extraordinary community. Together, we won't just launch products-we'll disrupt entire markets.
At SharkNinja, Diversity, Equity, and Inclusion are vital to our global success. Valuing each unique voice and blending all of our diverse skills strengthens SharkNinja's innovation every day. We support ALL associates in bringing their authentic selves to work, making an impact, and having the opportunity for career acceleration. With help from our leadership, associates, and our community, we aim to have equity be a key component of the SharkNinja DNA.
Learn more about us:
Life At SharkNinja
Outrageously Extraordinary
SharkNinja Candidate Privacy Notice
- For candidates based in all regions, please refer to this Candidate Privacy Notice.
- For candidates based in China, please refer to this Candidate Privacy Notice.
- For candidates based in Vietnam, please refer to this Candidate Privacy Notice.
We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, disability, or any other class protected by legislation, and local law. SharkNinja will consider reasonable accommodations consistent with legislation, and local law. If you require a reasonable accommodation to participate in the job application or interview process, please contact SharkNinja People & Culture at [email protected]
SharkNinja Needham, Massachusetts, USA Office
89 A Street, Needham, MA, United States, 02494
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
