Artificial Intelligence Developer jobs in Delhi at CryptoMize are open on a rolling, always-hiring basis. This is a full-time, permanent engineering position with immediate joining at our Recent Delhi HQ, building the machine-learning systems the practice’s platforms run on. Analysts here model; researchers here explore; developers here make it real — services, pipelines and inference infrastructure that survive production traffic across the nine-platform stack. You will build high-performance ML applications and the data infrastructure beneath them, from feature stores to serving layers, with the uptime that client engagements demand. The complete job description — responsibilities, requirements, seniority path and selection process — follows.

LOCATION New Delhi (HQ)

EMPLOYMENT Full-time · Permanent

AVAILABILITY Immediate · Rolling intake

COMPENSATION Discussed at screening

TRACKS ON THIS DESK26

CRAFT SKILLS NAMED11

TOOLS & SYSTEMS5

PATH STAGES4

01

01The actual work

What will you actually do as a Artificial Intelligence Developer at CryptoMize?

01

Build and operate production ML services — training pipelines, inference APIs and monitoring — on the practice’s platform stack

02

Engineer the data infrastructure: ingestion from platform corpora, feature stores, versioned training sets

03

Take validated models from notebook to service: containerized, tested, observable, and honest about drift

04

Optimize for the real constraints — latency, GPU cost, throughput on streaming media and sentiment workloads

05

Build simulation and what-if tooling that lets strategists interrogate model behavior before it ships

06

Keep the ML platform operable: reproducible environments, model registries, rollback paths

07

Collaborate with analysts on model handoff and with platform teams on integration contracts

ROLE RESPONSIBILITIES

As an Artificial Intelligence Developer you will build high-performance machine-learning applications and the supporting infrastructure — platforms, pipelines and simulation solutions — that the practice’s intelligence products run on. The measure is production:



services that survive traffic, models that ship, and systems colleagues can operate without paging you.

You will develop across Linux and cloud environments, work with GPU-class hardware where the workloads demand it, and apply distributed-computing tools as datasets outgrow single machines. Data management is part of the craft: mining and analysis methods, model building, algorithms and simulations maintained as living, versioned assets.

Collaboration runs both ways — receiving validated models from analysts with clean handoff contracts, and integrating with platform teams on interfaces that hold. Client data flowing through your systems is confidential without exception.

02

02Capability profile

What skills and tools does a Artificial Intelligence Developer need?

Craft skills11

Tools & systems5

Offer standards4

Production Python — typed, tested, reviewable servicesML engineering: training pipelines, batch and streaming inference, model versioningPyTorch/TensorFlow serving — optimization and quantization for real constraintsData engineering — ingestion, feature stores, dataset versioningContainerization and orchestration (Docker, Kubernetes basics)Linux development discipline and cloud environments (AWS-class)GPU hardware literacy — profiling and cost-aware workload placementAPI design (REST) and NoSQL/RDBMS schema judgmentObservability — logging, metrics and drift monitoring for live modelsCode review and Git-based team workflowDiscretion with client data flowing through systems you build (NDA-grade)

Python 3.11 (PyTorch, FastAPI)Docker + KubernetesPostgreSQL and Redis-class storesAWS or equivalent cloud (EC2/SageMaker-class)MLflow-class registry and tracking





Depth of demonstrated skill in the specific role disciplineClassification and scope of the client engagement the role supportsUrgency and time-sensitivity of active project requirementsTrack record built across CryptoMize engagements

Also known as: ai developer jobs · machine learning engineer · artificial intelligence engineer · ml developer

03

03Seniority ladder

Artificial Intelligence Developer — seniority path at CryptoMize

Engineering careers advance on what stays up: systems that survive production, models that ship, and infrastructure colleagues trust.

- Artificial Intelligence Developer

Owns services and pipelines for one to two platform workstreams with senior review.

1/4

- Senior Artificial Intelligence Developer

Designs ML system architecture, leads production standards, and mentors junior engineers.

2/4

- AI Engineering Lead

Runs the engineering side of the platform — architecture, reliability and the developer bench.

3/4

- AI Practice Principal

The apex: owns the practice’s AI capability end-to-end — research direction, production systems and delivery.

4/4

04

04The engagement surface

CryptoMize work a Artificial Intelligence Developer touches

Every role plugs into live engagements across the five Penta-P domains — these are the services your work feeds.

Artificial Intelligence Developer · Job Opening

This seat plugs into 7 live CryptoMize services across the five Penta-P domains — the work below is where yours lands.

7 SERVICESPENTA-P

- AI Governance
- Predictive Intelligence
- Big Data Mining
- Data Security
- Cybersecurity
- IT Consultancy
- Intelligence

WHAT DOES ARTIFICIAL INTELLIGENCE DEVELOPER COMPENSATION DEPEND ON?

Compensation is discussed during screening — never a fixed public figure, because it varies per person and per engagement. It depends on:

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OFFER CONSTRUCTION FACTOR

01

Depth of demonstrated skill in the specific role discipline

02

Classification and scope of the client engagement the role supports

03

Urgency and time-sensitivity of active project requirements

04

Track record built across CryptoMize engagements

📌 Artificial Intelligence Developer (India)
🏢 Crypto Mize
📍 India