Role Description: o Design and develop ML systems: Choose the right algorithms, designing data pipelines, and building scalable models. o Data preparation and feature engineering: Gather, clean, and transform data into a usable format for training models. o Model training and evaluation: Train models on the prepared data, evaluating their performance using metrics, and fine-tuning them to achieve optimal results.o Model deployment and monitoring: Deploy models into production on-prem or on cloud infrastructure, ensuring their reliability and performance, and monitoring their performance over time. o Collaboration: Work with data scientists, software engineers, and domain/business experts to develop and implement ML solutions.

Essential Skills: o Strong experience with Deep Learning and NLPo Hands on working knowledge of interfacing with LLM APIs and LLM agents, prompts and responseso Strong programming skills in languages such as Python, java, or C++. Experience with cloud platforms (AWS, GCP, and Azure) and MLOps tools.o 3+ years of hands-on experience in machine learning development, and experience leading a team of machine learning developers or engineers.o Strong understanding of software development principles, including design patterns, testing, and deployment. o Experience with DevOps practices such as CI/CD, experience with containerization using Docker and Kubernetes.o Strong understanding of application implementation requirements, including risk, privacy, and compliance.o Excellent communication and leadership skills, with the ability to work effectively with cross-functional teamso Previous experience with MLOps orchestration tools such as AirFlow, KubeFlow, Dagster, Flyte, or MetaFlow;o Familiarity with machine learning frameworks such as PyTorch, TensorFlow and/or similar

Desirable Skills: o Familiarity with Snowflake, Airflow, or similar orchestration and warehousing platformso Understanding of CI/CD principles, version control, and production deployment best practices