Research Scientist, Operations Research; Infrastructure Lab

Research Scientist, Operations Research (Infrastructure Lab)

Location:

Seattle

Team:
Infrastructure

Employment Type:

Regular

Job Code: A122886A

About the Team:
We are the Infrastructure System Lab — a hybrid research and engineering group building the next-generation AI-native data infrastructure. Our work sits at the intersection of databases, large-scale systems, and AI. We drive innovation across guided areas:
Next-generation databases, AI for infra, LLM Copilot, high-performance cache systems.

About the Role:

We are seeking a highly motivated and technically strong Research Scientist with a PhD in Computer Science, Database, Information Retrieval, or a related field to join our team. Your work will directly contribute to the next-generation vector database infrastructure that supports real-time and offline retrieval across billions or even trillions of high-dimensional vectors.

Why Join Us:

• Work on problems at the frontier of AI x systems with huge practical impact.
• Collaborate with a world-class team of researchers and engineers.
• Opportunity to publish, attend conferences, and contribute to open-source.
• Competitive compensation, generous research support, and a culture of innovation.

Responsibilities:

• For scenarios such as AI data centers and cloud resource scheduling, understand business requirements, formulate mathematical models, and design and develop efficient algorithms, heuristic algorithms, and meta-heuristic algorithms for optimization problems.
• Explore AI for OR by integrating LLM, RL and Agent technologies into the operations research optimization pipeline, including but not limited to:
  Natural language-based decision engine interfaces & Enhancing the interpretability of optimization results.

Minimum Qualifications:

• Ph.D. degree with strong research achievements, such as multiple first-author papers at conferences (CCF-A) in the areas of Data, Systems, or AI.
• Solid foundation in operations research theory, with expertise in areas such as linear programming, integer programming, and combinatorial optimization.
• Proficient with at least one mainstream commercial or open-source solver (e.g. Gurobi, CPLEX, CP-SAT).
• Familiar with commonly used (meta-)heuristic algorithms (e.g. genetic algorithms, simulated annealing) and experienced in real-world deployment.
• Strong engineering and coding skills, proficient in at least one programming language such as Python, C++, or Java, with solid knowledge of common data structures and algorithms.
• Excellent logical thinking and business abstraction skills, capable of translating ambiguous business requirements into clear technical solutions.
• Strong communication, teamwork, and collaboration abilities.

Preferred Qualifications:

• Domain knowledge of datacenter hardware supply chain operations or the underlying implementation of cloud computing products.
• Familiarity with LLMs, reinforcement learning, and Agent frameworks such as Lang Graph.
• Experience with prompt engineering optimization and Agent development.
• Strong interest and insight in combining traditional operations research optimization with generative AI.

The base salary range for this position in the selected city is $148,200 - $300,960 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these…