Manager/Senior Manager of Machine Learning

This role is onsite 5 days a week in Fremont, CA

Responsibilities

• Lead and mentor a team of Machine Learning (ML) engineers and researchers, fostering a high-performance culture and driving innovation.
• Oversee the design, development, and deployment of scalable ML models and systems, optimizing performance across e-commerce platforms.
• Define and drive the end-to-end ML lifecycle, including data collection, model training, validation, deployment, monitoring, and improvement.
• Collaborate with cross-functional teams, including product management, engineering, and business stakeholders, to align ML initiatives with company goals.
• Develop ML solutions for recommendation systems, personalization, ranking, and demand forecasting.
• Optimize ML infrastructure, ensuring efficient resource utilization and scalability, including leveraging cloud-based ML environments.
• Establish and enforce model governance, data privacy, and compliance frameworks within ML workflows.
• Drive research and innovation in ML techniques, leveraging deep learning, reinforcement learning, and generative AI for business impact.
• Partner with business leaders to define key metrics and success criteria for ML models, ensuring alignment with broader business objectives.
• Stay up to date with the latest ML advancements and assess their applicability to the company’s business problems.

Required Qualifications

• Bachelor’s, Master’s, or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related field.  
• 6+ years of experience in building and deploying ML models at scale, with at least 2+ years in a leadership role managing ML teams.  
• Strong experience in ML frameworks such as TensorFlow, PyTorch, JAX, or Scikit-learn.  
• Proficiency in programming languages like Python.  
• Hands-on experience with cloud-based ML services (AWS SageMaker, GCP Vertex AI, Azure ML).   
• Strong knowledge of feature engineering, model explainability, bias mitigation, and ethical AI practices.  
• Experience with ML applications in e-commerce, including recommendation systems, search ranking, fraud detection, and demand forecasting.  
• Experience in GPU acceleration, high-performance computing, or ML model optimization.  
• Experience working with graph neural networks, deep reinforcement learning, or generative AI.  
• Familiarity with business intelligence tools and data visualization for ML insights.  
• Contributions to open-source ML projects or published research in ML-related fields.  
• Excellent communication and collaboration skills, with the ability to articulate complex technical concepts to non-technical stakeholders.

Benefits

• Comprehensive health insurance package, including medical, dental, and vision.  PPO/HMO packages
• 401k, 4% company match
• Equity and Bonus 
• Vacation, sick and holiday time off
• Monthly mobile stipend
• Monthly Weee! Points credits

Compensation Range

• The US base salary range for this full-time position is $185,000 - $243,000
• This role may be eligible to discretionary bonus, incentives and benefits 
• Our salary ranges are determined by role, level, and location

The range displayed on each job posting reflects the minimum and maximum base salary for new hires for the position across all US locations. Within the range, individual pay is determined by multiple factors like job-related skills, experience and work locations. Your recruiter can share more about the specific salary range during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include any variable compensation elements.

Weee! is an equal opportunity employer welcoming all qualified applicants regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status or any other basis prohibited by law.  Discrimination or harassment of any kind is not tolerated at Weee!. If you need to inquire about an accommodation or need assistance with completing the application, please email us at applicantaccommodation@sayweee.com.

For more jobs and to find out more about Weee!, visit our career page: https://about.sayweee.com/careers