Artificial Intelligence Developer

CryptoMize; Dive Anjur; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

CryptoMize in New Delhi HQ is hiring a full-time AI Developer to build production ML services, data pipelines and inference infrastructure. You will work on training pipelines, feature stores and serving layers, ensuring uptime for client engagements and scalable platforms.

The role requires hands-on experience with Python-based ML engineering, model versioning, containerization, and cloud environments, with exposure to PyTorch or TensorFlow serving. Immediate joining is possible.

Qualifications

• Experience building production ML services, pipelines and inference APIs.
• Experience with data ingestion, feature stores and training data versioning.
• Familiarity with containerized ML services and cloud deployment.

Responsibilities

• Build and operate production ML services — training pipelines, inference APIs and monitoring — on the practice’s platform stack
• Engineer the data infrastructure: ingestion from platform corpora, feature stores, versioned training sets
• Take validated models from notebook to service: containerized, tested, observable, and drift-aware

Skills

Production Python

ML engineering

Data engineering

Containerization

Linux development

Tools

Python 3.11

Docker

Kubernetes

PostgreSQL

Redis

AWS

Job description

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 New 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.

What you will actually do:

• Build and operate production ML services — training pipelines, inference APIs and monitoring — on the practice’s platform stack
• Engineer the data infrastructure: ingestion from platform corpora, feature stores, versioned training sets
• Take validated models from notebook to service: containerized, tested, observable, and honest about drift

Skills that matter: Production Python, ML engineering: training pipelines, batch and streaming inference, model versioning, PyTorch/TensorFlow serving, Data engineering, Containerization and orchestration (Docker, Kubernetes basics), Linux development discipline and cloud environments (AWS-class).

Tools you will use: Python 3.11, Docker + Kubernetes, PostgreSQL and Redis-class stores, AWS or equivalent cloud.

Location: New Delhi (HQ), E4, Vasant Vihar. Type: full-time permanent. Availability: immediate, rolling intake. Compensation: discussed at screening.