Machine Learning Engineer

About ProductNow

ProductNow is building the world’s best operating system for AI-native teams, where agents and humans align, build, and ship together. Our mission is to solve the hardest problem in execution: alignment. Today, fragmented tools, workflows, and endless meetings are what teams rely on to get on the same page. We believe there’s a better way.

We’re creating an AI-native execution operating system: a unified workbench with virtual teammates (PN agents) that offload repetitive tasks, capture organizational context, and help teams accelerate execution. By getting people aligned more quickly, ProductNow empowers humans to focus on what matters most: creativity, judgment, and collaboration.

Our first step is to meet users where much of their work already happens: in documents. We’re reimagining the document experience from the ground up, with LLMs at the core. The result is a unified, AI-native writing platform that, when paired with PN agents, blends human creativity with intelligent virtual teammates. These teammates generate content, capture context, and remove busywork—creating a faster path to alignment and a more joyful way of working.

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

• 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.

Logistics

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

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

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

• Inclusivity: We encourage you to apply even if you don’t meet every single qualification. We prioritize strong working relationships, mentorship, and giving people opportunities to grow, especially with today’s rapidly evolving AI tools. Diversity is at the heart of our engineering team, and we know you’ll feel that when you meet us.

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

How we’re different

• Experienced leadership: Our leaders and advisors have lived this problem for over 20 years inside some of the world’s largest institutions. They bring both maturity and a proven understanding of how to create and maintain an efficient, professional work environment.

• Cutting-edge engineering: Our team pairs deep, modern AI expertise with imaginative thinking to design alignment-focused systems that feel fresh and forward-looking.

• Strong distribution: We have access to diverse channels that allow us to reach the right customers quickly and effectively.

• Defensible strategy: Our execution strategy is solid and validated, built to withstand competition from big labs, big tech, and other startups. With unique insights into how the underlying technology works, and how to seamlessly integrate it with existing software, we’re positioned to create experiences that are not just functional, but truly delightful.

Join the journey!

At ProductNow, we’re building more than just an execution OS; we’re building a team that thrives on alignment, collaboration, and shared purpose. Our engineering culture is rooted in living our values: ensuring everyone is aligned on the direction of the product and that every voice is heard.

We offer competitive compensation, meaningful ownership, and the chance to play a pivotal role on our rocketship. Along the way, you’ll find a supportive team, deep opportunities for growth, and plenty of moments for connection and bonding.