Lead Machine Learning Ops Engineer at BJ's Wholesale Club

Marlborough, Massachusetts, United States

Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Retail, WholesaleIndustries

Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field
Minimum of 4-6 years of experience in machine learning or MLOps
Strong knowledge of ML algorithms (e.g., XGBoost, Prophet, matrix factorization, multi-armed bandit)
Experience with model lifecycle management, including tracking, packaging, versioning, and deployment using tools such as MLflow
Strong programming skills with Python and PySpark (preferred)
Experience with CI/CD pipelines, automation tools, and practices
Proficiency in monitoring tools and performance optimization techniques
Experience with engineering and development collaboration tools such as GIT/Jira/Confluence
Familiarity with cloud platforms (like AWS) and Databricks (preferred)
Strong analytical and problem-solving skills
Excellent verbal and communication skills

Build, deploy, and manage machine learning models using applied statistics (supervised/unsupervised learning, feature selection, etc.)
Translate complex ML concepts and findings for non-technical audiences
Develop and implement scalable ML deployment strategies, ensuring models are production-ready
Monitor, retrain, and fine-tune models in production to maintain optimal accuracy and performance
Design and maintain robust ML infrastructure, including data pipelines and model serving infrastructure
Ensure infrastructure supports high-volume data processing and model training
Implement and manage MLOps tools to support the end-to-end workflow
Establish monitoring systems and alerts to track model performance and health
Proactively address production issues related to model accuracy, drift, and latency
Continuously optimize models and pipelines for cost, speed, and scalability
Work closely with Business, data scientists, engineers, and IT teams to ensure seamless integration of ML models into production systems
Collaborate with cross-functional teams to understand business requirements and translate them into ML solutions
Mentor junior team members and promote best practices in model development and deployment