Data Operations Analyst

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 throughout. 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. Data Operations Analyst

We are looking for an eager and motivated Data Operations Analyst to join our Data Operations team. At Deploy, our DataOps team is responsible for supporting the development of our proprietary AI models leveraging our Deploy Data platform to deliver high-quality training and testing datasets. Day to day, you will be managing multiple projects at a time with operational excellence by analyzing priorities, metrics, and deliverables. Our ideal candidate is interested in learning the ins and outs of a fast growing startup, as they will play an essential part in the product development lifecycle. You will also have the opportunity to work in a collaborative and close knit team. This is a great opportunity to see how a high growth startup functions in action. \n Responsibilities

Create, set up, and audit projects on the Deploy Data platform to support internal Product and ML initiatives and power proprietary Deploy Models

Own and execute projects by creatively identifying ways our data solutions can advance model performance, product capabilities, and internal objectives

Ensure projects run smoothly by managing timelines, identifying challenges, and proactively resolving issues while keeping stakeholders informed

Collaborate with Product and ML teams at the start of each project to understand scope, technical requirements, and success criteria

Collaborate with engineers in order to set up optimal pipelines and efficiently audit projects

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

Bachelor's degree

0-2 years of work experience

You are highly organized and detail-oriented; you handle multiple priorities without missing a beat

You have excellent written and verbal communications skills with an analytical mindset

You have demonstrated success in a competitive environment

You are highly self-motivated and ambitious in achieving goals

You are a strong team player, but can work and execute independently

You are driven and actively seek opportunities to contribute -- no one needs to push you to excel

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Who We Are

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! The current expected base salary for this position ranges from $60,000 - $85,000. 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.