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AI / ML

Hire senior AI engineers from Bangladesh.

From RAG pipelines to fine-tuning to agent loops — production systems, not notebooks. Evals you can trust, latency budgets you can ship against, and prompts you don't have to keep rewriting.

Capabilities

What our AI engineers do.

  • RAG done right

    Hybrid retrieval, re-ranking, chunking strategies tuned to your corpus. Eval-driven, not vibes-driven.

  • Agent systems

    Tool-using agents with proper guardrails, retries, and human-in-the-loop where it matters.

  • Fine-tuning + distillation

    When base models aren't enough — LoRA, full fine-tunes, distillation to smaller models.

  • Evals + observability

    Offline + online evals, token-level cost tracking, regression testing for prompt changes.

Default stackPyTorchLangChainOpenAIAnthropicvLLMPinecone· We adapt to your stack — these are starting points, not constraints.

How fast

Hire in 7–10 days.

From brief to first commit. We move when you move.

  1. 01

    Day 1–2

    Brief us. We shortlist 2–3 vetted candidates against your stack and seniority bar.

  2. 02

    Day 3–5

    Interview the shortlist. Pair on a real problem from your codebase if you want.

  3. 03

    Day 6–7

    Pick. We handle paperwork, NDA, equipment, and access.

  4. 04

    Day 8–10

    Ship. Your new engineer commits in their first week, not their first month.

FAQ

Common questions.

What models do they work with?
Frontier models (Claude, GPT, Gemini), open-weights (Llama, Mistral, Qwen), and self-hosted via vLLM.
Do they handle MLOps?
Yes — separate from but adjacent to data science. They own the production lifecycle.

More roles

Other engineers we place.