I'm hiring for both EM and Senior EM levels building the automation layer for freight pricing, matching, onboarding, and settlement. Lead 1-3 teams (FTE + contractors), own delivery end-to-end, ~8 yrs exp typical. I expect all managers to be technical and be able to help unblock the team, though your day-to-day wont be in the code.
Interesting problems: trust/fraud at marketplace scale; legacy-data-meets-modern-stack; and all kinds of problems that come with powering hundreds of billions of dollars worth of transactions every year.
AI/LLM: We are leaned in, but still hold humans responsible for what they push and expect everyone to review and understand llm output before asking other humans to look at a thing.
Culture: I am deeply familiar with Google's project oxygen/aristotle and am building a culture where our teams can do great work with minimal bs.
Location: Must be local to one of our three locations (Seattle, Portland, Denver)
Primary Tech: Node/TS, React, GraphQL, Kafka/redpanda, k8s, AWS, etc
https://careers.dat.com/jobs/?gh_jid=6139594004
Reach out directly at <fname>.<lname>+hn@dat.com; I am the hiring manager for these roles. Human emails will get human responses.
My profile and background: https://www.linkedin.com/in/kelvin-luu/
We're building a heterogeneous execution platform to accelerate data analytics and ML workloads, and we're looking for a deep kdb+/q expert to work alongside our hardware acceleration team. You'll focus on kdb+ internals, query optimization, and the C API, helping us understand how queries execute under the hood, where the bottlenecks are, and how to integrate acceleration into kdb+ workflows.
Looking for: expert-level kdb+/q, engine internals, query planning/optimization, C API extensions, performance analysis. Nice to have: exposure to hardware acceleration concepts.
Apply: email amir@silicon45.com with your resume and a short note on 1-2 performance-critical kdb+ systems you personally built or optimized.