Staff ML Engineer (LLM)

We are seeking a Staff ML Engineer with a focus on productizing LLM and building Agents to join our team. This role involves designing, developing and working with structured and semi-structured data to build an overall Agentic framework capable of completing a set of tasks to complete user requests. The ideal candidate will have extensive (4-6 years') experience in Natural Language Processing (NLP), Machine Learning/Deep Learning, MLOps, understanding of LLMs and a history of successful deployments of Deep Learning or Machine Learning solutions.

Responsibilities:

• Assist in architecting Agent roles and functionalities for the backend application.
• Conduct research with other team members to evaluate and determine which LLM to utilize for different Agents.
• Create and refine conversation prompts to refine Agent capabilities with few-shot examples.
• Participate in code reviews and provide constructive feedback to team members.
• Mentor team members and provide technical guidance
• Stay up to date with topics like Agentic AI, LLMs and Deep Learning to help improve our product.

Requirements:

• Bachelor's degree in computer science, engineering, or a related field
• Proven 3 years of experience as a Machine Learning Engineer (MLE)/Sr. MLE or similar roles.
• Proficiency in Python and SQL is required, plus knowledge of one or more programming languages such as Java, C or JavaScript.
• Proficient in PyTorch/Tensorflow, NumPy and Pandas.
• Demonstratable experience in using Hugging Face models and Transformers library for custom application deployment, via finetuning or prompt engineering.
• Experience working with various cloud providers such as AWS, GCP or Azure to deploy and monitor Deep Learning/Generative AI products.
• A solid understanding of Git, Kubernetes, Redis, Kafka and PostgreSQL
• Excellent communication, interpersonal skills and willingness to go the extra mile to build a great product.

Preferred Qualifications

• Master’s degree or above in computer science, engineering or related field.
• Experience building Agentic AI applications with open-source models such as BERT, QWEN or LLAMA.
• Knowledge of linguistics or cognitive science.
• Publications or contributions to the field of deep learning, or NLP.