Role Overview
As an ML Engineer at OpenRouter, you'll be at the forefront of integrating and optimizing large language models (LLMs) for a diverse range of applications. OpenRouter provides a unified API, abstracting away the complexities of interacting with various LLM providers. Your role will involve enhancing the performance, reliability, and cost-efficiency of these integrations, contributing directly to a platform that empowers developers to build cutting-edge AI products. This is a highly technical role requiring deep expertise in machine learning, distributed systems, and API development, with a strong focus on practical application and scalability.
Key Responsibilities
- Develop and maintain robust integrations with various LLM providers and models.
- Optimize LLM inference performance, latency, and cost through techniques like caching, batching, and model selection.
- Design and implement monitoring, logging, and alerting systems for LLM performance and API health.
- Research and evaluate new LLMs and machine learning techniques to enhance platform capabilities.
- Collaborate with product and engineering teams to define and deliver new features and improvements for the OpenRouter API.
Required Skills
Strong proficiency in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow). Deep understanding of large language models, their architectures, and inference optimization techniques. Experience with API design and development (RESTful, GraphQL). Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes). Solid understanding of distributed systems and microservices architecture. Excellent problem-solving skills and ability to work in a fast-paced, startup environment.
Interview Process
The interview process typically begins with an initial recruiter screen, followed by a technical phone screen focusing on Python and ML fundamentals. Subsequent rounds often include a coding challenge, a system design interview (with a focus on ML system design and API architecture), and a behavioral/culture fit interview with a hiring manager or team lead. Expect discussions around your experience with LLMs, distributed systems, and your approach to optimizing complex ML pipelines.
Salary & Compensation
The salary range for an ML Engineer at OpenRouter is typically between $160,000 and $250,000 annually, depending on experience, skill set, and performance. Compensation packages often include competitive base salary, equity options (stock options or restricted stock units), and comprehensive benefits such as health insurance, paid time off, and a flexible work environment. As a rapidly growing startup, there's potential for significant equity upside.
Why Join
Joining OpenRouter offers a unique opportunity to work at the intersection of cutting-edge AI and robust API infrastructure. You'll be part of a small, high-impact team building foundational technology that enables thousands of developers to innovate with LLMs. The fast-paced environment, direct impact on product, and exposure to a wide array of LLMs and use cases make it an exciting place for an ML Engineer passionate about scalable AI solutions. You'll have significant autonomy and the chance to shape the future of LLM integration.
Tips for Applicants
- Deep Dive into LLMs: Understand not just how to use LLMs, but their underlying mechanisms, common challenges (e.g., hallucination, prompt engineering), and optimization strategies.
- Highlight API & System Design: Showcase experience in building and scaling APIs, especially those interacting with complex external services or ML models.
- Demonstrate Practical Impact: Be ready to discuss specific projects where your ML engineering work led to measurable improvements in performance, cost, or reliability.