Netomi: Data Scientist - II — Gurugram

About Netomi

Netomi develops an agentic-AI platform for enterprise customer experience. Its employer introduction describes no-code tools for creating and managing AI agents across customer interactions. The platform connects automation with the practical workflows used by customer-service organisations. Recruitment material also describes agentic workflows, prompt engineering and API-based automation around that platform. The business is therefore concerned with how AI agents perform tasks within customer journeys, as well as the software used to build and operate them.

The position and its setting

Netomi lists Data Scientist - II in Gurugram, under reference f24c0390-c103-4609-b8e4-abab0aca928c. The details below separate the work described by the employer from essential conditions, preferred experience and practical preparation advice.

• Department: Product Engineering
• Employment type: Full-time
• team: Data Science

Responsibilities and work described

• Do you believe in the missions Intelligence agencies?
• Are you interested in solving complex programmatic and technical issues?
• If you are interested in working on some of the most challenging technical and programmatic issues, we are interested in talking to you about Netomi work and career opportunities
• We are seeking a Senior Data Scientist with deep expertise in Large Language Models (LLMs) and modern AI systems to join our team
• This role combines cutting-edge research, rapid prototyping, and production-grade implementation to deliver innovative AI-powered solutions
• Drive NLP and machine learning projects from conception through deployment, working as both a direct contributor and key technical advisor
• Research & Innovation - Stay current with the latest LLM research, architectures, and advancements in the field including real-time models and multimodal systems
• Evaluate emerging techniques and methodologies for potential application to business problems
• Monitoring: developments in transformer architectures, fine-tuning approaches, model optimization, and real-time inference
• Research and assess new LLM capabilities, frameworks, and API features as they emerge
• Solution Design & Prototyping - Identify and define approaches for complex AI challenges leveraging state-of-the-art LLMs
• Design: and build proof-of-concept solutions to validate technical feasibility
• Rapidly prototype LLM-based applications using modern frameworks and orchestration tools
• Research / execution: rigorous experiments to evaluate different approaches and methodologies
• Work: collaboratively in multi-disciplinary team environments and establish professional networks with subject matter experts
• Production Development & Software Engineering - Write clean, maintainable, production-quality code following software engineering best practices and design patterns

Essential requirements and candidate background

• 3-5 years of experience in data science, machine learning, and AI development with focus on NLP and LLM applications
• Bachelor's/Master's or higher degree in Computer Science, Machine Learning, Statistics, or related technical field
• Track record of building and deploying production ML/AI systems from research to deployment
• Mastery of Python with software engineering fundamentals (OOP, design patterns, testing)
• Deep hands-on experience with LLM frameworks and APIs (OpenAI, Anthropic, or similar)
• Experience: at least one deep learning framework (PyTorch or TensorFlow)
• Proficiency: modern ML orchestration and agentic frameworks (LangGraph, CrewAI, LangChain, or similar)
• Understanding: NLP techniques: embeddings, information extraction, semantic search, classification
• Experience: diverse ML models: neural networks, transformers, SVM, Random Forest, clustering, Bayesian models
• Experience: advanced LLM features: tool calling, function calling, multi-turn conversations, structured outputs
• Knowledge: software development practices: version control (Git), testing (pytest)
• Experience: REST APIs, async programming, and building scalable backend services
• Familiarity: vector databases and embedding systems (Pinecone, Weaviate, FAISS, or similar)
• Knowledge: distributed computing, cloud platforms (AWS, GCP, or Azure), and containerization (Docker)
• Experimental design skills with ability to formulate hypotheses and conduct rigorous analysis
• Problem-solving abilities and intellectual curiosity to stay current with AI research
• Self-motivated with ability to work collaboratively in multi-disciplinary teams

Preferred experience and additional strengths

• Experience: voice/speech models and real-time audio processing (OpenAI Realtime API or similar)
• Knowledge: MCP (Model Context Protocol) and emerging LLM standards
• Experience: MLOps tools and practices (model monitoring, versioning, A/B testing)
• Contributions to open-source ML/AI projects or published research papers
• Familiarity: streaming architectures and event-driven systems (Kafka, RabbitMQ)

Location, schedule and contract conditions

• Work arrangement: Remote
• Advertised location: Gurugram

Pay and application dates

A verified salary figure is not established in this article. An online estimate for another Data Scientist - II vacancy is not an offer for reference f24c0390-c103-4609-b8e4-abab0aca928c; use the employer’s own pay disclosure and recruitment communication.

A closing date is not confirmed in this article. Check the current employer page before submitting: an undated posting can change or be withdrawn.

How to apply to Netomi

Applications follow the official employer page linked below.

Open the official Netomi posting below and match the title and reference f24c0390-c103-4609-b8e4-abab0aca928c.

Compare your qualifications and experience with the essential conditions for the Gurugram position, then read the preferred criteria separately.

Prepare an accurate CV and the supporting items requested in that employer’s application. Provide only information and documents you are authorised to share.

Use the employer’s application option, complete the required fields and review the submission. Retain the acknowledgement when one is provided. Job Alerts World does not receive the application.

Practical preparation: Python

Python work is easier to assess through a concrete example than a list of libraries. Explain the problem, the input data, the parts you implemented and how you checked the output. Include a repository or a short technical note when you can share it.

Relevant skills

• Python
• Kafka
• Docker
• AWS
• GCP
• Azure
• MCP
• REST APIs
• APIs
• AI/ML
• LLMs
• machine learning
• AI
• Google Cloud
• Git