Staff / Principal Machine Learning Engineer

TL;DR

Staff / Principal Machine Learning Engineer (AI): Responsible for researching, building, optimizing, and deploying the production ML systems that power our platform with an accent on quality, latency, and cost-effectiveness. Focus on the difficult research and engineering problems of building the engine for the next generation of AI-driven software.

Location: Must be based in or relocate to Mountain View, California, USA

Salary: $240,000 - $385,000+ bonus + equity + benefits

Company

Inworld's technology has powered experiences from companies such as NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella and Bible Chat.

What you will do

• Experiment with and implement cutting-edge ML models and techniques to advance our core AI capabilities.
• Train, evaluate, and optimize production-scale models and systems, focusing on quality, latency, cost, and on-device constraints.
• Collaborate with product and backend teams to translate novel ideas and research findings into robust, production-ready solutions.

Requirements

• A PhD in a relevant technical field, or a BA/BS degree with equivalent research and/or engineering experience.
• 5+ years of combined experience in software development (Python, C++) and applied ML engineering.
• Demonstrated experience applying or researching ML in domains such as natural language processing, speech processing, and/or action planning.
• Strong foundation in data structures, algorithms, and neural network architectures.
• Proficiency with ML frameworks such as PyTorch.

Nice to have

• A passion for learning and staying up-to-date with the latest advancements in ML research and its applications.
• Ability to work collaboratively in a fast-paced environment with shifting priorities.
• Familiarity with pre-training, fine-tuning, RLHF and evaluation of large language and speech models.
• Knowledge of working with embedded systems and/or running ML on edge devices.
• Strong background in mathematics and/or physics.

Culture & Benefits

• We believe in the power of in-person collaboration to solve the hardest problems and foster a strong team culture.