Machine Learning Engineer

ProductNow • Palo Alto, CA

1d • Hybrid

About The Position

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.

Requirements

• 1+ internship or project-based experiences in ML, applied AI, or data science. (Full-time professional ML experience not required.)
• Familiarity with Python, ML frameworks (such as PyTorch or TensorFlow), and basic data processing workflows.
• Excited to see how ML can directly improve user-facing experiences, not just research for its own sake.
• Hungry to take responsibility, follow through on projects, and grow into increasing levels of independence.
• Eager to deepen your expertise in ML techniques, model deployment, and AI systems while building real-world products.
• Comfortable working closely with engineers, PMs, and designers to co-create solutions.
• Thrives in a fast-paced environment with shifting priorities, and welcomes feedback as a way to accelerate growth.
• Values diversity of thought, seeks input from others, and contributes to a supportive, collaborative team culture.

Nice To Haves

• Exposure to large language models or generative AI is a plus.

Responsibilities

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern