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AI engineers who ship to production

Dedicated AI and ML engineers who have deployed agents, RAG systems and predictive models, not researchers with notebooks, engineers with pager duty.

Dedicated senior. Your tools, your standups, your repo, two week paid trial to start.

One rate: AI & ML

₹1,14,000/ month

Dedicated senior · 3 month commitment · saves ₹6,000 monthly

  • Dedicated senior engineer, yours only
  • Two week paid trial to start
  • Your tools, your standups, your repo
  • Free instant replacement, anytime

The role, plainly.

Serious AI work is engineering: retrieval over real data, evaluation suites that catch regressions, guardrails that hold under live traffic, and cost-aware inference that survives its own bill. That is the profile we vet for.

Start with one engineer or a full pod, architect, engineer and data engineer working as your team, on your roadmap, in your standups. Your data stays in your cloud; you own every model and every line from the first commit.

What they bring

  • LLM applications

    Agents, RAG pipelines, evaluation suites and guardrails that survive real traffic.

  • Predictive models

    Forecasting, recommendation and anomaly models monitored in production.

  • Data engineering

    Pipelines and feature stores that feed models reliably, versioned like code.

  • MLOps

    Deployment, drift monitoring and retraining loops so models stay honest.

What they take on.

The work this role lands most often, select a slot to open it. Every engagement runs on the same model.

Typical engagement

Custom AI agents & copilots

Agents grounded in your data with tool calling, guardrails and human escalation designed in.

AI & ML, slot one

From call to first commit.

Fast where it can be, careful where it must be, and reversible at every step.
  1. Share your needs

    A 30 minute call to understand the role, stack and team fit.

  2. Meet matched engineers

    We shortlist within 48 hours; you interview whoever you want.

  3. Two week paid trial

    Work together on real tasks. Not a fit? Replace or walk away.

  4. Onboard and scale

    Same engineers long term. Add or reduce with 30 days notice.

The stack

  • Python
  • LangChain
  • PyTorch
  • pgvector
  • Airflow
  • MLflow
  • FastAPI
  • AWS

Why teams hire this way.

The advantages that show up in the first month, and the ones that compound.
  • Production scars

    Engineers who have run models under real load, on call, for years. They design for failure from day one.

  • Business first

    Every model ties to a metric you track. No science projects on your budget.

  • Full stack around the model

    APIs, dashboards and integrations come from the same team, not a handoff.

  • Transparent rates

    One monthly rate per engineer. No recruitment fees, no benching charges.

Asked about hiring ai & ml.

The questions teams raise before starting, answered plainly.

A question we missed?

Typically within two weeks of your first call. Senior profiles are shared within 48 hours, and most clients interview the same week.

The first two weeks are a paid trial. If the fit is wrong, we replace the engineer or you stop, no questions asked.

Yes. Dedicated means dedicated: your engineer works exclusively on your product, in your tools and standups.

You do, from the first commit, including training code and evaluation sets.

AI & ML Engineers, frequently asked questions

Explore further.

Other roles that pair with this one, and the project service behind the same discipline.

Trained, leashed, shipping.

our robots stay friendly on a short retrieval lead.

Doodles from the studio, drawn the way we build, by hand

Ready to hire ai & ml?

One 30 minute call, stack, mission, start date. Matched profiles in 48 hours, and the two week trial keeps it reversible.

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