What are the responsibilities and job description for the Senior Machine Learning Product Architect position at Stelvio Inc.?
Senior Machine Learning Product Architect
Location: San Diego, CA (Hybrid)
We’re seeking a Senior Machine Learning Product Architect to lead the architectural vision for AI, ML, and GenAI capabilities across a large-scale technology platform. This role operates at the intersection of product strategy and technical design, shaping how intelligent systems are conceived, built, and scaled. You’ll collaborate closely with engineering, product, and domain experts to deliver high-impact, production-ready AI solutions.
Responsibilities
- Architect scalable ML and GenAI systems spanning training, inference, workflow automation, and production integration.
- Translate business objectives into AI-driven solutions in partnership with product leaders.
- Balance enterprise-grade standards with forward-looking, fit-for-purpose architectures.
- Lead strategic solution design while providing deep technical insight and mentorship when needed.
- Create architectural references, reusable patterns, and best practices.
- Drive MLOps and GenAI infrastructure initiatives, including model versioning, monitoring, and CI/CD pipelines.
- Collaborate with data scientists and ML engineers on diverse model workflows (ML, DL, GenAI, multi-modal).
- Champion AI/ML adoption and serve as a trusted technical advisor across the organization.
- Assess emerging technologies and propose scalable, sustainable solutions.
- Support governance, compliance, and security initiatives for responsible AI use.
- Optimize AI workloads for reliability, performance, and cost efficiency.
Qualifications
- Bachelor’s or Master’s in Computer Science, AI/ML, or a related field.
- 8 years of experience building and deploying production-grade AI/ML systems.
- Proven track record scaling ML and GenAI architectures from concept to production.
- Strong knowledge of ML algorithms, LLMs, embeddings, RAG, and GenAI pipelines.
- Proficiency in Python.
- Strong understanding of software architecture principles and design patterns.
- Excellent communication skills and ability to engage diverse stakeholders.
- Cloud or ML/GenAI certifications (preferred).
- Portfolio showcasing impactful AI/ML deployments.