Associate Product Manager, Deploy Models

About Deploy:

Deploy is an intelligence infrastructure platform that gives developers and enterprises access to open source and proprietary AI models. For leading open source LLMs, Deploy operates an optimized model inference engine that keeps costs and latency low while maintaining high throughput. Deploy also offers a set of proprietary AI models that address challenges in content safety, AI & deepfake detection, sponsorship intelligence, and IP & publicity protection. Trusted by the world's largest and most innovative organizations, Deploy's solutions unlock high-performance AI model inference at production scale.

Deploy has raised more than $200M from leading investors, including Tomales Bay Capital, General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. The company has more than 250 employees across offices in San Francisco, Seattle, New York, and Delhi.

Associate Product Manager, Deploy Models Role:

As an Associate Product Manager on our Deploy Models team, you will work cross-functionally with stakeholders to help define product requirements and support implementation efforts, collaborating closely with our Machine Learning, Core Infrastructure, and Product teams. You will play an important role in the core of our business: our cloud-hosted deep learning models. You will help support Deploy's growth by contributing to our innovative capabilities and building a strong foundation for future ownership within the product org.

Responsibilities:

• Support the roadmap, functional requirements, and development timeline for our Deploy Models, under the guidance of senior PM/leadership
• Develop an understanding of our customers' needs across various industries
• Assist in product execution from inception to delivery
• Help engineering and product teams break down projects into manageable parts, and help track progress against delivery plans
• Support our Deploy Models portfolio by learning the needs of the product development teams, and contributing to the creation of our deep learning models that provide human-like interpretation of video, image, audio, and text
• Help communicate product benefits to our users and internal stakeholders
• Work with senior product and engineering stakeholders to help define new features and improve models habitually
• Help track engineering velocity and support the identification of best practices to improve delivery speed and security
• Maintain awareness of industry best practices for data maintenance handling as it relates to your role
• Adhere to policies, guidelines, and procedures pertaining to the protection of information assets
• Report actual or suspected security and/or policy violations/breaches to an appropriate authority

Requirements:

• You have a Bachelor of Science in Computer Science, Engineering, or similar field
• You have some hands-on exposure to modern machine learning libraries, frameworks, and technologies (coursework, internships, or professional experience)
• You have excellent verbal and written communication and presentation skills
• You have a working knowledge of functional programming languages such as Python or Node.JS
• You have 0-2 years of combined Machine Learning and Product Management experience
• You are comfortable with, and can thrive in, an environment that is constantly changing, frequently uncertain, and at times chaotic
• You are detail-oriented, organized, collaborative, and hands-on
• You are eager to grow into a leadership role, with an interest in eventually owning team goals and deadlines
• Beyond just shipping new products, you obsess about continuous product improvement

Compensation:

The current expected base salary for this position ranges from $90,000 - $120,000. Actual compensation may vary depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here.