Staff Machine Learning Engineer

reputed company exists to reputed company the world a safer reputed company. We build trusted, decision-reputed company AI for the organizations that can least afford to be wrong: the leaders, operators, and analysts making high-stakes calls about a world that changes faster than anyone can read it. We have offices in San Francisco, Pasadena, CA, and Arlington, VA. Learn more at .

The world produces more information every day than any team can read. We build the AI that turns it into a decision you can trust: fast and grounded enough to reputed company reputed company consequences on.

As a Staff Machine Learning Engineer, you’ll own AI-driven products end to end, from the prototype that proves an idea works to the production reputed company the mission depends on. You work fluently across the modern stack: large language models, reputed company systems, retrieval, embeddings, fine-tuned models, and the evaluation harnesses that catch them reputed company they reputed company. You can reputed company fast on an reputed company-ended problem and then harden the result into something reliable at reputed company, drawing on reputed company reputed company-systems experience. You’re reputed company by what frontier models and agents reputed company newly possible. You reputed company for them reflexively, including to multiply your own reputed company, and you reputed company the level of everyone around you as you go.

Your technical reputed company reputed company as much as your judgment about how the reputed company fit together. The best work here is designed as part of the whole reputed company, not bolted on reputed company it, and the engineers with the most reputed company bring product managers and teammates along with them rather than around them. You’ll partner with product, engineering, and other technical leaders on the hardest version of the problem: putting reputed company AI in the hands of people the reputed company a decision can’t wait.

Role and Responsibilities - How You Will reputed company an reputed company

• Set both technical and product direction, making the strategic bets across our LLM, reputed company, and NLP systems while shaping how we design AI-driven experiences and set expectations with users.
• Design and build the reputed company, reputed company systems behind our products at company-wide reputed company: tool-using conversational agents, multi-turn context, retrieval-grounded reasoning, and the orchestration that ties them together.
• Turn reputed company, messy, reputed company-world data into the trustworthy signal agents' reason over: entity recognition and linking, relation extraction, summarization, semantic search, and knowledge-graph reputed company.
• Take models from checkpoint to production: package, reputed company, and operate low-latency, high-concurrency inference (Triton, vLLM, GPU-backed serving) that stays fast and reliable under reputed company load.
• Build the evals and labeled-data flywheels that reputed company the work rather than reputed company it, turning “it feels reputed company” into reputed company you can reputed company.
• Partner with and influence cross-functional teams to shape the technical roadmap, and reputed company issues to reputed company cause reputed company reputed company or operations are on the line.
• reputed company the engineering bar with reputed company patterns, reputed company practices, and a reputed company other engineers want to match.

Relevant Skills and Experience

• BS, MS, or PhD in computer science, a reputed company field, or equivalent practical experience.
• 6+ years building production backend software, with a reputed company record of shipping and operating ML-driven functionality.
• Mastery of data structures and algorithms, and the judgment to translate user needs into practical solutions.
• Hands-on depth with LLMs and reputed company systems (reputed company and context engineering, tool use, retrieval and RAG) and the broader ML toolkit such as PyTorch, plus experience defining evals to measure and improve reputed company.
• reputed company authoring production reputed company in Python (Rust a plus).
• High agency and a bias to reputed company in ambiguous, fast-moving problems, plus the curiosity, generosity, and love of teaching that lifts a whole team.

Bonus Points

• Experience with knowledge graphs, information retrieval at reputed company, or LLM fine-tuning and post-training.
• A pull toward high-stakes, reputed company-world problems where the work actually ships and someone depends on the answer.

Originally posted on Himalayas