Machine Learning Engineer

ProductNow builds AI teammates that eliminate coordination overhead in product teams. We help teams stay aligned, make better decisions, and move faster—together.

What makes ProductNow different is that we’re multiplayer-first. We’re not building tools just to make individuals faster, but systems that help entire teams think, decide, and execute as one.

We’re a team of experienced builders and industry leaders from Google, Microsoft, Amazon, Palantir, Adept, and Verkada. We work on the problems we’re solving every day—and we’re building ProductNow for ourselves.

If you’re excited about tackling real coordination challenges, building intelligent systems, and learning how high-impact products get built at scale, you’ll feel at home here.

In this role, you will

• Explore and experiment with state-of-the-art AI models and machine learning techniques, contributing to core product features powered by ML.

• Own projects end-to-end – from understanding problem requirements and designing experiments to building prototypes, iterating, and helping bring them into production.

• Collaborate with product, design, and engineering teams to translate user needs into ML-powered solutions.

• Dive deep into data, building an understanding of how to measure model performance and improve real-world outcomes.

• Stay curious and up to date with emerging ML research, applying learnings to improve our product and stack.

• Contribute to a culture of rapid experimentation, balancing scrappy prototypes with thoughtful iteration.

• Learn from senior engineers, while taking initiative to independently explore new approaches and technologies.

• Bring a strong ownership mentality – driving projects forward, unblocking yourself, and pushing ideas from concept to execution.

You may be a good fit if you

• Education: Bachelor’s degree in a related field, or equivalent practical experience.

• Experience: 1+ internship or project-based experiences in ML, applied AI, or data science. (Full-time professional ML experience not required.)

• Technical skills: Familiarity with Python, ML frameworks (such as PyTorch or TensorFlow), and basic data processing workflows. Exposure to large language models or generative AI is a plus.

• Product focus: Excited to see how ML can directly improve user-facing experiences, not just research for its own sake.

• Ownership mindset: Hungry to take responsibility, follow through on projects, and grow into increasing levels of independence.

• Learning-first attitude: Eager to deepen your expertise in ML techniques, model deployment, and AI systems while building real-world products.

• Collaboration: Comfortable working closely with engineers, PMs, and designers to co-create solutions.

• Adaptability: Thrives in a fast-paced environment with shifting priorities, and welcomes feedback as a way to accelerate growth.

• Inclusive mindset: Values diversity of thought, seeks input from others, and contributes to a supportive, collaborative team culture.

Our stack

• Core: Monorepo • TypeScript • Turbo • Bun • Biome

• Frontend: Next.js • Redux • Radix • Auth0

• Backend: NestJS • Prisma • Postgres

• Infrastructure: AWS • CDK • Vercel

• Dev Tools: Cursor • Claude • Graphite • GitHub • Loom • Linear

• Location: Hybrid - we’re in the office in Palo Alto, CA near the Caltrain station from Tuesday to Thursday, with Mondays and Fridays remote.

• Work Authorization: At this time, we are unable to sponsor new visas, but we encourage you to check back soon, as this may change.