Principal PM: AI Model Training & Fine-Tuning

Seekr; Menlo Park (CA); Hybrid; USD 190,000 - 235,000; Full time

Benefits offered by this job

RSUs

Unlimited PTO

Hybrid work (Reston, VA & Austin, TX)

401(k) with company match

Healthcare (medical, dental, vision)

Job summary

Seekr is seeking a Principal Product Manager to lead model training and fine-tuning capabilities within SeekrFlow. You will own the product strategy, roadmap, and execution for how customers customize and operationalize models at scale for enterprise deployments.

You will collaborate with ML, software engineering, infrastructure, and field teams to deliver production-ready capabilities with strong governance, reliability, and performance.

Qualifications

• 8+ years of product management experience for technical platforms.
• Strong understanding of AI/ML product development workflows (training, fine-tuning, evaluation, deployment).
• Ability to reason through tradeoffs across model quality, data quality, cost, performance, usability and production readiness.
• Experience collaborating with ML engineers, platform engineers, infrastructure teams, design teams, and developer-focused product teams.

Responsibilities

• Define the product vision, strategy, and roadmap for model training and fine-tuning within SeekrFlow.
• Partner with engineering and design to build, launch, and iterate on product capabilities across the training lifecycle.
• Translate complex ML workflows into clear, usable platform experiences for technical and enterprise users.
• Work with cross-functional teams to identify high-impact problems to solve and determine success metrics.

Skills

8+ yrs PM

AI/ML product

Tradeoff reasoning

Cross-functional

Strong communication

Enterprise products

Platform product

Product discovery

Job description

Seekr is seeking a Principal Product Manager to lead model training and fine-tuning capabilities within SeekrFlow. You will own the product strategy, roadmap, and execution for how customers customize and operationalize models at scale for enterprise deployments.

You will collaborate with ML, software engineering, infrastructure, and field teams to deliver production-ready capabilities with strong governance, reliability, and performance.