Level AI

Optimizes call center data with AI

Senior Machine Learning Engineer - NLP

Natural Language Processing & LLMsConfirmed live in the last 24 hours

Full-timeNo salary listedHybrid

About the Job

Requirements

A B.Tech, M.Tech, or PhD in computer science or mathematics-related fields from a tier-1 engineering institute, plus 3+ years of industry experience in Machine Learning and NLP.
Strong coding skills in Python and PyTorch, with familiarity with Transformers and LangChain/LangGraph.
Strong practical experience with NLP problems such as text classification, entity tagging, information retrieval, question-answering, natural language generation, and clustering.
Knowledge and hands-on experience with Transformer-based language models such as BERT, Llama, Qwen, Gemma, and DeepSeek.
In-depth familiarity with LLM training concepts, model inference optimizations, and GPUs.
Experience deploying machine learning and deep learning models using REST APIs, Docker, and Kubernetes.
Problem-solving skills involving data structures and algorithms.

Responsibilities

Understand customer needs and apply machine learning techniques to build data-driven solutions.
Work on NLP problems in areas such as voice agents, agentic applications, text classification, entity extraction, and summarization using LLMs.
Collaborate with cross-functional teams to integrate or upgrade AI solutions in company products and services.
Optimize existing machine learning models for performance, scalability, and efficiency.
Help implement and evaluate reasoning, planning, and memory modules for agents.
Build, deploy, and own scalable production NLP pipelines.
Build post-deployment monitoring and continual learning capabilities.
Propose suitable evaluation metrics and establish benchmarks.
Keep up with state-of-the-art techniques in the area and exchange knowledge with colleagues.
Learn, implement, and apply emerging model architectures such as LLMs, inference optimizations, distributed training, and open-source models.

Desired Qualifications

Knowledge of cloud platforms such as AWS, Azure, or GCP and their machine learning services.
Knowledge of multimodal models.
Knowledge of real-time streaming tools or architectures such as Kafka and Pub/Sub.
Experience with open-source LLMs such as LLaMA and Mistral.
Basic understanding of vector search, RAG, and prompt engineering.
Contributions to AI side projects or GitHub repositories.
Exposure to vector databases or retrieval pipelines such as FAISS and Pinecone.

Level AI was founded in 2019 and is a Series C startup headquartered in Mountain View, California. Level AI revolutionizes customer engagement by transforming contact centers into strategic assets. Our AI-native platform leverages advanced technologies such as Large Language Models to extract deep insights from customer interactions. By providing actionable intelligence, Level AI empowers organizations to enhance customer experience and drive growth. Consistently updated with the latest AI innovations, Level AI stands as the most adaptive and forward-thinking solution in the industry.

Empowering contact center stakeholders with real-time insights, our tech facilitates data-driven decision-making for contact centers, enhancing service levels and agent performance. As a vital team member, your work will be cutting-edge technologies and will play a high-impact role in shaping the future of AI-driven enterprise applications. You will directly work with people who've worked at Amazon, Facebook, Google, and other technology companies in the world. With Level AI, you will get to have fun, learn new things, and grow along with us. Ready to redefine possibilities? Join us!

We'll love to explore more about you if you have

Big picture: Understand customers’ needs and innovate and use cutting-edge Machine Learning techniques to build data-driven solutions.
Work on NLP problems across areas such as voice agents, agentic applications, text classification, entity extraction, and summarisation, using LLMs.
Collaborate with cross-functional teams to integrate/upgrade AI solutions into company’s products and services
Optimise existing machine learning models for performance, scalability and efficiency.
Help implement and evaluate reasoning, planning, and memory modules for agents.
Build, deploy and own scalable production NLP pipelines.
Build post-deployment monitoring and continual learning capabilities.
Propose suitable evaluation metrics and establish benchmarks.
Keep abreast of SOTA techniques in your area and exchange knowledge with colleagues.
Desire to learn, implement and apply latest emerging model architectures (like LLMs), inference optimizations, distributed training, using open-source models, etc.

Your role at Level AI includes but is not limited to

B.Tech/M.Tech/PhD in computer science or mathematics-related fields from tier-1 engineering institutes with 3+ years of industry experience in Machine Learning and NLP.
Strong coding skills in Python and Pytorch with familiarity with libraries like Transformers and LangChain/LangGraph.
Strong practical experience in NLP problems in areas such as text classification, entity tagging, information retrieval, question-answering, natural language generation, clustering, etc.
Knowledge and hands-on experience with Transformer-based Language Models like BERT, Llama, Qwen, Gemma, DeepSeek, etc.
In-depth familiarity with LLM training concepts, model inference optimizations, GPUs, etc.
Experience with ML and Deep Learning model deployments using REST API, Docker, Kubernetes, etc.
Good problem-solving skills involving data structures and algorithms.
Knowledge of cloud platforms (AWS/Azure/GCP) and their machine learning services is desirable.
Knowledge of multimodal models is a plus
Knowledge of real-time streaming tools/architectures like Kafka and Pub/Sub is a plus.

Bonus Points

Experience with open-source LLMs (LLaMA, Mistral, etc.)

Basic understanding of vector search, RAG, and prompt engineering concepts

Contributions to AI side projects or GitHub repos

Exposure to vector databases or retrieval pipelines (e.g., FAISS, Pinecone)

To learn more visit : https://thelevel.ai/

Funding : https://www.crunchbase.com/organization/level-ai

LinkedIn : https://www.linkedin.com/company/level-ai/

About the Company

Level AI

Optimizes call center data with AI

Level AI provides software that improves customer experience and operational efficiency in the BPO sector by integrating human and machine intelligence. Its platform unifies call center data from multiple sources and uses intelligent automation and machine learning to automate tasks, guide decisions, and improve interactions, all delivered through a subscription model. It differentiates itself by offering end-to-end data integration across silos and blending human expertise with ML to boost sales conversions and QA productivity in call centers. The goal is to help BPO providers deliver better customer experiences while making operations more efficient and cost-effective.

Company size: 201-500
Company stage: Acquired
Total funding: $74.4M
Headquarters: Mountain View, CA
Founded: 2018

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