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  • Seen live on NK Securities Research's site 2 days ago
  • Mid level
Pay
Not stated
Location
Gurugram, Haryana, India
Open for
12+ days
First seen
Oct 23, 2026

Posting record

No flags

Open 12+ days

The posting's record, oldest first
  1. NK Securities Research's site dates the posting
  2. Ghostless first sees this listing
  3. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking NK Securities Research, so its true age is longer.

Last checked Nov 3, 2026.

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What the posting discloses

Not stated: Pay, real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Some employers add pay only on their own site. Check the original posting before you rule it out.

Skills mentioned

About the role

NK Securities Research is a leading financial firm that leverages cutting-edge technology and sophisticated algorithms to trade the financial markets. Founded in 2011, we have gained invaluable experience in the field of High-Frequency Trading (HFT) across different asset classes.

Role Overview

We’re looking for engineers who can take AI work beyond experiments and make it hold up in production. You’ll work closely with quant researchers and infra engineers to build AI systems that actually get used improving research speed and internal tooling without slowing down the core stack. We value engineers who think about trade-offs, test what they build, and care about how things run in production.

What You’ll Build

Production AI

  • Ship models that meet defined latency and reliability expectation
  • Add monitoring, rollback, and guardrails before anything goes live
  • Optimise inference across CPU/GPU environments when it matters

Integration into Real Systems

  • Plug AI into data-heavy workflows without hurting performance
  • Work within existing low-latency architecture instead of fighting it
  • Profile and remove bottlenecks rather than guessing

AI for Engineers & Researchers

  • Build tools that genuinely speed up research and development
  • Improve code understanding, review workflows, and internal knowledge retrieval
  • Keep systems auditable and predictable

LLM & Retrieval Systems

  • Implement structured RAG and embedding pipelines with validation in place
  • Create safe integration layers between models and internal systems

Performance & Standards

  • Track latency, drift, and stability — not just accuracy
  • Build observability into everything you ship
  • Help raise the bar for how AI is engineered here

What We’re Looking For

Strong Python fundamentals

  • Clear thinking around system design and performance trade-offs
  • Experience deploying AI systems in production (1–5 years is typical)
  • Familiarity with transformers, embeddings, or LLM deployment

Nice to have

  • Exposure to C++ / Rust / Go
  • Experience in distributed or performance-critical environments
  • Comfort operating with ownership and minimal hand-holding

Why This Role

  • You’ll build AI systems that directly impact research and infrastructure
  • You’ll work with engineers who argue about trade-offs — and care about getting them right
  • You’ll have real ownership from design to deployment

What We Offer

  • Competitive salary package.
  • A dynamic, high-performance, and collaborative work environment.
  • Strong focus on career growth and development.
  • Catered breakfast and lunch.
  • Monthly team dinners.
  • Annual international and domestic team trips.

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