Founding Machine Learning Engineer

🚀 Founding Engineer (Machine Learning Engineering Focus)

Early-Stage AI Company | Enterprise Focus | Hands-On Builder

Fully in office in San Francisco

Experience: 3-5 years

🌐 About the Company

Shields Group Search is partnering with a breakout, venture-backed AI company that is quietly emerging as one of the most compelling infrastructure plays in its category.

The company has raised $7.5M in Seed funding from top-tier Silicon Valley funds and a highly selective group of operator-angels. Their backers include investors and founders affiliated with firms and ecosystems such as Y Combinator, a16z, Founders Fund, Sequoia-backed companies, and senior leaders from some of the most successful AI and enterprise software companies of the past decade. The cap table is stacked with people who have built and scaled category-defining platforms before and know exactly what it takes to do it again.

They already have real production traction, paying enterprise customers, and a product actively running in demanding environments. The company has also turned down multiple acquisition offers, choosing to stay independent and build something much larger. They are now gearing up for a Series A, with a clear mandate to harden their systems, scale responsibly, and evolve what they have built into a truly enterprise-grade platform.

The team is now expanding its core engineering group and looking to bring on a Founding Engineer who will play a key role in shaping the product, architecture, and engineering culture from an early stage.

🧠 The Role

This role is best suited for a hands-on Machine Learning Engineer with real-world experience deploying, tuning, and maintaining ML models in production. While the team works on enterprise-grade AI systems, this hire is not primarily focused on on-prem enterprise deployments. Instead, the emphasis is on practical MLE execution, curiosity, and the ability to build and iterate quickly.

As a Founding Engineer, you will work closely with the founders to translate research and ideas into scalable, production-grade systems. This is a builder role for someone who enjoys writing code, learning fast, and growing alongside the company.

🔧 What You’ll Do

• Build, deploy, and iterate on machine learning models in real production environments
• Own model deployment workflows, tuning, evaluation, and performance optimization
• Collaborate closely with founders on product direction and technical architecture
• Write high-quality, production-ready code across ML systems and supporting infrastructure
• Help establish early engineering best practices while remaining deeply hands-on
• Contribute across the stack as needed in a fast-moving early-stage environment

✅ What We’re Looking For

Must-Haves

• 3–5 years of professional experience in software engineering, ML engineering, or applied ML research
• Strong MLE background with hands-on experience deploying and tuning models in production
• Demonstrated ability to write real production code, not just prototypes or research artifacts
• Experience working with modern ML frameworks and deployment workflows
• High curiosity, strong learning aptitude, and comfort operating in ambiguity

Nice-to-Haves

• Applied ML research experience with a strong implementation bias
• Early-stage startup experience
• Exposure to AI infrastructure, model monitoring, or reliability tooling

🌟 Why This Role

• True founding-level impact at a mission-driven AI company
• Direct collaboration with technical founders
• Ownership over core ML systems from day one
• Opportunity to grow into a senior technical leader as the company scales
• Competitive compensation and meaningful equity

🎯 Ideal Candidate Profile

This role is a great fit for someone who:

• Identifies as an MLE who loves building, not just theorizing
• Enjoys translating research ideas into working systems
• Wants early ownership and long-term growth
• Is excited to grow alongside a company tackling foundational AI problems