Lead Machine Learning Ops Engineer

Join our team of more than 34,000 team members, supporting our members and communities in our Club Support Center, 235+ clubs and eight distribution centers. BJ’s Wholesale Club offers a collaborative and inclusive environment where all team members can learn, grow and be their authentic selves. Together, we’re committed to providing outstanding service and convenience to our members, helping them save on the products and services they need for their families and homes.

The Benefits of working at BJ’s

•        BJ’s pays weekly

•        Eligible for free BJ's Inner Circle and Supplemental membership(s)*

•        Generous time off programs to support busy lifestyles* 

                      o Vacation, Personal, Holiday, Sick, Bereavement Leave, Jury Duty

•        Benefit plans for your changing needs*

                      o Three medical plans**, Health Savings  Account (HSA), two dental plans, vision plan, flexible spending ​

•        401(k) plan with company match (must be at least 18 years old)

*eligibility requirements vary by position

**medical plans vary by location

Job Summary:

We are seeking a Lead MLOps Engineer with a strong foundation in data science principles with background in machine learning operations. This role is ideal for someone who can bridge the gap between model development using data science principles and production deployment, ensuring scalable, robust, and efficient ML solutions. You will work closely with other data scientists, engineers, IT, and business partners to build, deploy enterprise-grade models, manage the full ML lifecycle, and mentor junior team members on best practices.

Key Responsibilities:

Model Development, Deployment & Lifecycle Management:

• 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

ML Infrastructure & Tooling:

• 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

Monitoring and Optimization:

• 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

Collaboration and Communication:

• 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

Job Requirements:

• Educational Background: Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
• Professional Experience: Minimum of 4-6 years of experience in machine learning or ML Ops.
• Technical Expertise:
  • 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 tool such as GIT/Jira/Confluence
  • Familiarity with cloud platforms (like AWS) and Databricks (preferred)

 Soft Skills:

• Problem-Solving: Strong analytical and problem-solving skills.
• Communication: Excellent verbal and written communication skills.
• Team Collaboration: Ability to work collaboratively in a cross-functional team environment.
• Adaptability: Ability to adapt to new technologies and rapidly changing environments.
• Detail-Oriented: Attention to detail and a commitment to delivering high-quality solutions.

This is a hybrid role. Tuesday through Thursday are in-office days at BJ's Club Support Center in Marlborough, MA and Monday and Friday are remote days.