Systems​/Infra​/Platform Engineer - Quant Trading Systems

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Batonics builds high‑throughput quantitative trading and research platforms and AI agents for leading funds and institutions across Asia, the U.S., and Europe. Our products deliver advanced market‑microstructure analytics, backtesting, portfolio and risk tools, and formal verification for low‑latency systems merging high‑performance computing, AI, and frontier quantitative research.

We’re looking for a part‑time engineer to help develop end‑to‑end quantitative trading and research systems including high‑frequency trading (HFT) platforms.

Your initial work will be on but feel free to explore

• Show me something you’ve built end‑to‑end (preferably using AI tools) and describe your stack.
  Send to
• Interview.
• Task(s) (1‑2hrs)
• (Optional) Go head‑to‑head with me where we both tackle a multi‑tier coding challenge (AI tools allowed).
• Follow‑up chat.
• Decision.

• High‑performance database systems & transactional correctness (isolation/serializability)
• Real‑time data pipelines & market‑data processing (ultra‑low latency, burst tolerance)
• Performance/latency optimization to sub‑millisecond: CPU cache/NUMA SIMD, vectorization, I/O tuning
• Backend/platform architecture & multi‑region reliability (failover, disaster recovery)
• SRE/reliability engineering: SLOs, load shedding, autoscaling, chaos testing, tracing
• GPU compute & numerical methods, plus floating‑point stability and mixed precision
• Formal methods & rigorous testing: model checking, property‑based testing, fuzzing
• Security: applied crypto (use of vetted libs), web/appsec, sandboxing (seccomp/App Armor), secrets/keys
• Distributed systems & consensus (Raft/Paxos), consistency models, back pressure, idempotency
• Build systems & developer tooling:
  Bazel/CMake, reproducible builds, hermetic CI, static analysis
• Supply‑chain hygiene: dependency pinning/lockfiles, SBOMs, provenance/attestations
• Infrastructure as Code:
  Kubernetes/Terraform with policy as code (OPA/Kyverno)

• Part‑time
• Remote work with occasional in‑person meetings
• Hourly pay initially, scaling with workload and contribution