Senior Lead Machine Learning Engineer (MLOps & Data Platform)
REMOTE
Duties: What you will do in this role:
· Facilitate and participate in the preparation of ML data sets and scoring processes
· Develop and maintain a knowledge of real-time and snapshotted data sources from across the company, as well as Analytics team members responsible for various sources
· Work with the Data Scientists to develop and implement key machine learning models
· Develop and support the ML portion of the Enterprise Data Platform strategy to maximize the distribution of ML predictions and recommendations, including API-based ML scoring and data warehouse-based access
· Incorporate workflows into ML Data Engineering processes, to automate, monitor, and produce alerts
· Implement performance tuning and query optimization
· Act as a resource to the Machine Learning team with regards to Data Lifecycle Management
· Keep pace with latest technology across various databases, data lakes, warehouses etc.
· Collaborate with Analytics team members to follow all documented architecture, design & deployment processes to ensure compliance with policies
· Design and develop scalable, reusable data models
Skills: To be successful in this role you have:
· Experience in Machine Learning, Data Engineering, ML Infrastructure, or related fields, with strong foundations in probability, statistics, and machine learning.
· Hands-on experience with Databricks, including Unity Catalog, and cloud ML platforms such as Azure ML Studio, AWS, or Google Cloud Platform.
· Experience building and scaling end-to-end ML systems, ETL/ELT pipelines, and data workflows using Python, NumPy, Pandas, and SQL.
· Experience building scalable APIs and microservices using FastAPI, with Snowflake or equivalent data warehouse technologies.
· Experience deploying production workloads using Docker and Kubernetes, with a strong understanding of scalable, reliable software engineering practices.
· Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, Statistics, or equivalent field, with strong communication and cross-functional collaboration skills.
Education: Skills & Background:
· Bachelor's degree in a technical field such as computer science, computer engineering or related field required
· 5+ years of experience as AI/ML Engineer
· Deep understanding of data science, including 5+ years of experience in the space
· Ability to work as part of a team, as well as work independently or with minimal direction
· Excellent written, presentation, and verbal communication skills
· Collaborate with data architects, modelers and IT team members on project goals
· Strong knowledge of SQL, Python, R, Snowflake
