Senior Machine Learning Engineer, NLP

You will be a vital team member at Level AI, a Series C startup headquartered in Mountain View, California, founded in 2019. Level AI specializes in transforming contact centers into strategic assets by leveraging advanced technologies like Large Language Models to extract deep insights from customer interactions. Your role will involve empowering contact center stakeholders with real-time insights to enhance service levels and agent performance. By working with cutting-edge technologies, you will play a high-impact role in shaping the future of AI-driven enterprise applications. Joining Level AI will provide you with the opportunity to work with experienced professionals from top technology companies and grow along with the team. Key Responsibilities: - Understand customers' needs and innovate using cutting-edge Machine Learning techniques to build data-driven solutions. - Work on NLP problems across voice agents, text classification, entity extraction, and summarization using Large Language Models. - Collaborate with cross-functional teams to integrate/upgrade AI solutions into the company's products and services. - Optimize existing machine learning models for performance, scalability, and efficiency. - Implement and evaluate reasoning, planning, and memory modules for agents. - Build, deploy, and own scalable production NLP pipelines. - Establish post-deployment monitoring and continual learning capabilities. - Propose suitable evaluation metrics and establish benchmarks. - Keep abreast of State of the Art (SOTA) techniques in your area and exchange knowledge with colleagues. - Learn, implement, and apply the latest emerging model architectures like Large Language Models (LLMs), inference optimizations, and distributed training. Qualifications Required: - 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. - Practical experience in NLP problems such as text classification, entity tagging, information retrieval, question-answering, natural language generation, clustering, etc. - Hands-on experience with Transformer-based Language Models like BERT, Llama, Qwen, Gemma, DeepSeek, etc. - 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. Additional Company Details: To learn more about Level AI, visit their website. For information about their funding, you can visit their Crunchbase page. Connect with Level AI on LinkedIn. You will be a vital team member at Level AI, a Series C startup headquartered in Mountain View, California, founded in 2019. Level AI specializes in transforming contact centers into strategic assets by leveraging advanced technologies like Large Language Models to extract deep insights from customer interactions. Your role will involve empowering contact center stakeholders with real-time insights to enhance service levels and agent performance. By working with cutting-edge technologies, you will play a high-impact role in shaping the future of AI-driven enterprise applications. Joining Level AI will provide you with the opportunity to work with experienced professionals from top technology companies and grow along with the team. Key Responsibilities: - Understand customers' needs and innovate using cutting-edge Machine Learning techniques to build data-driven solutions. - Work on NLP problems across voice agents, text classification, entity extraction, and summarization using Large Language Models. - Collaborate with cross-functional teams to integrate/upgrade AI solutions into the company's products and services. - Optimize existing machine learning models for performance, scalability, and efficiency. - Implement and evaluate reasoning, planning, and memory modules for agents. - Build, deploy, and own scalable production NLP pipelines. - Establish post-deployment monitoring and continual learning capabilities. - Propose suitable evaluation metrics and establish benchmarks. - Keep abreast of State of the Art (SOTA) techniques in your area and exchange knowledge with colleagues. - Learn, implement, and apply the latest emerging model architectures like Large Language Models (LLMs), inference optimizations, and distributed training. Qualifications Required: - B.Tech/M.Tech/PhD in computer sc