Netomi

Enterprise AI for autonomous customer service

Data Scientist 2

AI Application EngineeringConfirmed live in the last 24 hours

Full-timeGurugram, Haryana, IndiaNo salary listedRemote

About the Job

Requirements

Three to five years of experience in data science, machine learning, and AI development, with a strong focus on natural language processing and large language model applications.
A Bachelor's, Master's, or higher degree in Computer Science, Machine Learning, Statistics, or a related technical field.
A proven track record of building and deploying production machine-learning and artificial-intelligence systems from research through deployment.
Mastery of Python and strong software engineering fundamentals, including object-oriented programming, design patterns, and testing.
Deep hands-on experience with large language model frameworks and application programming interfaces such as OpenAI or Anthropic.
Strong experience with at least one deep learning framework, such as PyTorch or TensorFlow.
Proficiency with modern machine-learning orchestration and agentic frameworks such as LangGraph, CrewAI, or LangChain.
A solid understanding of natural language processing techniques, including embeddings, information extraction, semantic search, and classification.
Experience with diverse machine-learning models, including neural networks, transformers, support vector machines, random forests, clustering, and Bayesian models.
Hands-on experience with advanced large language model features, including tool calling, function calling, multi-turn conversations, and structured outputs.
Strong knowledge of software development practices, including version control with Git and testing with pytest.
Experience with REST application programming interfaces, asynchronous programming, and building scalable backend services.
Familiarity with vector databases and embedding systems such as Pinecone, Weaviate, or FAISS.
Knowledge of distributed computing, cloud platforms such as AWS, GCP, or Azure, and containerization with Docker.
Strong experimental design skills and the ability to formulate hypotheses and conduct rigorous analysis.
Ability to work collaboratively in multidisciplinary teams.

Responsibilities

Stay current with the latest large language model research, architectures, and advancements, including real-time models and multimodal systems.
Evaluate emerging techniques and methodologies for potential application to business problems.
Monitor developments in transformer architectures, fine-tuning approaches, model optimization, and real-time inference.
Research and assess new large language model capabilities, frameworks, and application programming interface features as they emerge.
Identify and define approaches for complex artificial-intelligence challenges using state-of-the-art large language models.
Design and build proof-of-concept solutions to validate technical feasibility.
Rapidly prototype large-language-model-based applications using modern frameworks and orchestration tools.
Conduct rigorous experiments to evaluate different approaches and methodologies.
Establish professional networks with subject matter experts.
Write clean, maintainable, production-quality code following software engineering best practices and design patterns.
Develop robust, scalable agentic workflows using orchestration frameworks such as LangGraph, CrewAI, or similar tools.
Implement advanced large language model features, including tool calling, function calling, structured outputs, and multi-turn conversations.
Build production-grade systems utilizing Model Context Protocol and other emerging standards.
Design and implement scalable, fault-tolerant architectures for real-time large-language-model-powered applications.
Conduct thorough code reviews and maintain high code quality standards.
Optimize code for performance, memory efficiency, and cost-effectiveness in production environments.
Design rigorous experiments to test hypotheses and validate model performance.
Develop evaluation frameworks for large language model outputs, system performance, and user experience.
Optimize prompt engineering strategies, fine-tuning approaches, and inference efficiency.
Conduct A/B tests, performance benchmarking, and statistical analysis.

Desired Qualifications

Experience with voice or speech models and real-time audio processing, such as the OpenAI Realtime API or similar.
Knowledge of Model Context Protocol and emerging large language model standards.
Experience with MLOps tools and practices, including model monitoring, versioning, and A/B testing.
Contributions to open-source machine-learning or artificial-intelligence projects or published research papers.
Familiarity with streaming architectures and event-driven systems such as Kafka or RabbitMQ.

About the Company:

Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, United, and others to enable agentic automation at scale across the entire customer journey. Our no-code platform delivers the fastest time to market, lowest total cost of ownership, and simple, scalable management of AI agents for any CX use case. Backed by WndrCo, Y Combinator, and Index Ventures, we help enterprises drive efficiency, lower costs, and deliver higher quality customer experiences.

Want to be part of the AI revolution and transform how the world’s largest global brands do business? Join us!

Job Description:

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. You will drive NLP and machine learning projects from conception through deployment, working as both a direct contributor and key technical advisor.

Job Responsibilities

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. Monitor 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. Conduct 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. Develop robust, scalable agentic workflows using orchestration frameworks (such as LangGraph, CrewAI, or similar). Implement advanced LLM features, including tool calling, function calling, structured outputs, and multi-turn conversations. Build production-grade systems utilizing Model Context Protocol (MCP) and other emerging standards. Design and implement scalable, fault-tolerant architectures for real-time LLM-powered applications. Conduct thorough code reviews and maintain high code quality standards. Optimize code for performance, memory efficiency, and cost-effectiveness in production environments
Experimentation & Optimization - Design rigorous experiments to test hypotheses and validate model performance. Develop evaluation frameworks for LLM outputs, system performance, and user experience. Optimize prompt engineering strategies, fine-tuning approaches, and inference efficiency. Conduct A/B tests, performance benchmarking, and statistical analysis

Requirements

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

Bonus

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

Netomi is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.

About the Company

Netomi

Enterprise AI for autonomous customer service

Netomi provides an enterprise AI platform that automates and optimizes customer service for large-scale, regulated industries. Its agentic AI watches real-time customer journeys and proactively resolves issues across chat, email, messaging, and voice, often without human help. The platform combines proprietary natural language understanding with no-code workflow automation, enabling rapid deployment and seamless integration with legacy systems, and it offers Auto-pilot for autonomous resolution and Co-pilot to assist human agents. It handles very high request volumes, maintains strong security standards (ISO 27001, SOC2, GDPR), and partners with Adobe to embed AI into software layers, aiming to reduce support costs and improve customer satisfaction.

Company size: 201-500
Company stage: Series C
Total funding: $147.5M
Headquarters: San Mateo, CA
Founded: 2016

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