A leading software development company in the United States is seeking a Mid-Senior Level Product Management professional. In this full-time role, you will design evaluation strategies for AI systems and manage the ML model lifecycle, ensuring alignment with production needs. Candidates should have 3-4 years of commercial experience delivering projects and deep familiarity with transformer architectures and model optimization techniques. This position offers a competitive salary and valuable benefits such as 401(k) and vision insurance.
Qualifications
3-4 years of commercial experience delivering projects end-to-end.
Deep familiarity with transformer pipelines and experimentation.
Hands-on experience developing or training transformer-based models.
Responsibilities
Design and lead evaluation strategy for AI systems.
Contribute to ML model lifecycle and deployment infrastructure.
Define and monitor operational metrics for production.
Skills
Model compression or optimization techniques
Hands-on Machine Learning deployment
Evaluation strategy for AI systems
Experience with transformer-based LLMs
Code reviews and feedback
Familiarity with transformer architecture
Operational metrics monitoring
Collaboration with analytics team
Infrastructure development for ML lifecycle
Commercial project delivery experience
Job description
Base pay range
$130,000.00/yr - $170,000.00/yr
Key Skills & Experience Required
Proven use of model compression or optimization techniques
Hands‑on deployment, production, and operation of Machine Learning models and pipelines at scale, including both batch and real‑time use cases.
Design and lead the evaluation strategy for our Agentic AI and RAG systems, turning customer workflows and business needs into measurable metrics and clear success criteria.
Hands‑on experience developing or training transformer‑based LLMs from scratch
Participate in code reviews, offering thoughtful, constructive feedback to maintain code quality, readability, and consistency.
Deep familiarity with transformer architecture, training pipelines, and experimentation
Define and monitor operational metrics (latency, cost, reliability) to ensure evaluations align with production and customer expectations.
Work with the analytics team & stakeholders to understand their objectives in support of formulating, optimizing, and productionising ML models
Contribute to expanding and improving the infrastructure to support all stages of the ML model lifecycle and deployment in a production environment.
3‑4 years of commercial experience delivering projects end‑to‑end