Job Description
Posting Type Hybrid
Job Overview At Relativity we make software to help users organize data, discover the truth, and act on it. Our e-discovery platform is used by more than 13,000 organizations around the world to manage large volumes of data and quickly identify key documents during litigation, internal investigations, and compliance projects.
We are looking for a Product Manager to own Relativity's AI platform, our internal set of tooling and technology that manages the AI lifecycle for internal teams. These teams rely on our AI Platform to access, build, test, deploy, and monitor AI models and products. You will collaborate closely with applied scientists, engineers, and product managers to understand their workflows and pain points related to AI product development and delivery. Ruthless prioritization based on data is your mantra.
A successful candidate will have a strong technical background as well as experience taking AI/ML products from experimentation to production. We are looking for someone who is energized by helping teams be more efficient in building and deploying AI products.
Job Description and Requirements Role Responsibilities Accelerate AI Innovation: - Faster time to value. Own the success of initiatives around reducing applied science experimentation cycle time and reducing the time it takes our AI teams to validate their products both in the lab and in production.
- Create self-service capabilities. Empower engineering and applied scientist teams to leverage our AI platform as easily as possible.
- Streamline AI/ML lifecycle. Identify and resolve bottlenecks in our AI/ML lifecycle across each of our AI life cycle testing environments.
Product Ownership & Strategy - Customer Centric. Run continuous discovery sessions with consumers of our AI platform (engineers, product managers, applied science) to uncover and test product opportunities.
- Define Success. Partner withEngineering and internal platform consumers to define quarterly OKRs (Objectives and Key Results) that articulate team goals.
- Measure success. Define and track success metrics to measure platform adoption, efficiency gains, and business impact.
Technical Expertise - Partner with engineering: Partner with your engineering team to ensure deliverables meet our high standards for scalability, reliability, observability, security, and AI ethics.
- Lead tradeoff decision-making: Through a strong understanding of AI/ML workflows, technologies, and data pipelines lead product tradeoff and scope discussions with engineering, other product managers, and applied science.
- Simplify complex topics: Translate technical conversations and decisions to less technical audiences, internal and external, to create clarity with stakeholders.
Team Collaboration - Share context : Clearly articulate the "why" behind product decisions to foster alignment and buy-in from internal and external stakeholders.
- Lead cross-functional initiatives : Drive and participate in various cross-functional programs, ensuring that your teams' work is represented well and contributing to overall program success.
- Partner to drive adoption: Ensure that internal teams understand our product priorities and delivery status while partnering with them to drive adoption from customers.
Preferred Qualifications: - Experience working closely with Applied Science team.
- Experience working with platform-related products or products consumed by internal stakeholders.
- Experience building products that incorporate Large Language Models as part of their pipeline.
- Experience collaborating with technology vendors to assess the impact of potential system upgrades on existing infrastructure, and to escalate problem when needed.
Mi nimum Qualifications: - 4+ years of experience in product management at a technology company.
- Solid understanding of software development lifecycle and agile methodologies.
- Knowledge and experience doing discovery & usability testing to gather customer feedback.
Relativity is committed to competitive, fair, and equitable compensation practices. This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives.
The expected salary range for this role is between following values:
$115,000 and $173,000
The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position.
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