Do you want to help define the future of delivering the company software to customers? Join the Insight & Release Technologies team to work on new technologies that will be used to deliver the company platforms to millions of customers.
Our team has a passion for innovation and engineering and is looking for individuals with a genuine enthusiasm for collaborating with others to solve sophisticated problems with a focus on the user experience.
Description
You will join a team working on the next generation of software release workflows that enable the software development lifecycle for an ever-growing number of platforms and teams contributing to software products. Our applications integrate with developers’ workflows to enable the software development lifecycle from integrating source code all the way to releasing the company platforms and assets to customers.
In this role, you will work on bringing AI to our developer productivity tools. You will be at the forefront of building intelligent, agentic systems that help the company engineers write better, higher-quality code. You will collaborate closely with data, platform, and infrastructure teams to identify high-impact opportunities where ML can meaningfully improve developer workflows.
- Design and build machine learning pipelines. Evaluate, integrate, and optimize ML models and agentic workflows.
- Develop intelligent systems that reason over code coverage data to surface meaningful insights, prioritize under-tested areas, and recommend targeted test strategies.
- Build and improve semantic code search capabilities that allow engineers to find relevant code, patterns, and examples across large-scale internal codebases using natural language and embedding‑based retrieval.
- Apply ML techniques to advance static analysis tooling, including smarter bug detection, vulnerability identification, and code smell classification, beyond what traditional rule‑based approaches can achieve.
- Partner with platform and product teams to deeply understand engineer pain points and translate them into practical, high‑impact ML solutions.
- Lead the design of generative AI solutions, optimize ML infrastructure, and guide the development of data preparation and model optimization strategies.
- Drive technical direction, facilitate alignment across organizations, and mentor engineers across the team.
Preferred Qualifications
- Experience with GenAI techniques or GenAI‑related concepts.
- Bachelor’s degree in Computer Science, Machine Learning, or equivalent practical experience.
Minimum Qualifications
- Experience in ML engineering and software development, including experience in system design, architecture, and shipping scalable software products.
- Strong software engineering fundamentals (APIs, system design, distributed systems, frameworks architecture).
- Experience leading technical project strategy and optimizing ML infrastructure.
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