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Business Analyst, Deploy Models

Hive

About Deploy

About Hive

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.

Business Analyst, Deploy Models

Responsibilities

  • 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.
  • As a Business Analyst on the Deploy Models team, you will work closely with our Machine Learning, Product, and Business Development teams to ensure successful client deployments of our products. A mix of product configuration, project management, and client success, this is a unique role that demands both technical competence as well as client management abilities. You will serve as the point person for major client engagements, taking on a wide range of responsibilities to ensure integration success.
  • Collaborate with engineering teams to ensure successful technical deployments
  • Write scripts to analyze technical performance of production machine learning models
  • Analyze customer submissions, data, and results to understand desired changes to the machine learning models
  • Generate APIs for use by customers by ensuring accuracy of the technical configurations of the machine learning models
  • Collaborate with the product team and other stakeholders to ensure customer needs are met, including resolving any technical issues that users run into while accessing our machine learning models
  • Collaborate with the product and engineering teams as needed for other technical aspects of product deployment with customers
  • 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's or graduate degree in Computer Science or a related field, such as Engineering or Mathematics
  • You have 1-3 years of work experience in a Product Management or Engineering role at a technology or technology consulting company
  • You have working knowledge of functional programming languages such as Python or Node.JS
  • You have experience in an interdisciplinary/cross-functional field. Added points for enterprise-technology, SaaS, client facing, or start-up experience
  • You have distinctive problem-solving skills and impeccable business judgment
  • You possess excellent written and verbal communication skills

Pay

The current expected base salary for this position ranges from $80,000 - $100,000. 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.

Benefits

  • We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Deploy, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company.
  • Thank you for your interest in Deploy and we hope to meet you soon!