About Level AI :

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.

Total Experience : 10 - 12 years

What you will do :

- 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.

Tech Stack & Requirements :

- 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/