MLOps Engineer II, Marlboro or Chelmsford, Full-Time, Hybrid

 

Schedule

Monday-Friday 8-5 (40 hours) Hybrid 5 days/month in-office

What You’ll Do

Summary/Objective:

The MLOps Engineer will play a crucial role in building, maintaining, and optimizing our machine learning infrastructure. Working closely with data scientists and data architects, will develop and maintain platforms that streamline the lifecycle of machine learning models, from creation and training to deployment and updates. The MLOps engineer expertise will ensure the scalability of these solutions across the organization, utilize industry best practices, adheres to standards, and create MLOps governance, empowering us to leverage AI/ML technologies more effectively.

Essential Functions:

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Collaborate with data scientists to automate and optimize the ML model development process.
• Design, implement, and maintain ML solutions, ensuring high performance, reliability, and scalability.
• Manage the end-to-end lifecycle of AI/ML projects, from data collection and model development to deployment and monitoring.
• Ensure best practices in MLOps and cloud solutions, particularly within the AWS ecosystem (Sagemaker, Redshift, AWS ETL processes).
• Guide the selection and application of the latest advanced analytics technologies in alignment with overarching technologic and data strategies.
• Stay abreast of the latest advancements in AI/ML technologies and methodologies, integrating them into our operations to enhance efficiency and effectiveness.
• Support the organization’s data science strategy, ensuring it aligns with enterprise strategic priorities and initiatives.
• Collaborate with business stakeholders to identify opportunities to use data science to support decision-making, enhance the member experience, improve efficiency, and drive business growth.
• Prepare presentations, visualizations, project documentation and reports as needed.
• Keep the organization’s mission, vision, and values at the forefront of decision making and ensures alignment of organization’s strategic plan.
• Conduct all job functions and responsibilities in accordance with all company Compliance, Information Security and Regulatory policies, procedures, and programs.

What You’ll Need

Education and Experience Requirements:

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.
• Minimum of 3 years of experience in applying actionable analytics to solve complex problems.
• Strong knowledge of AI/ML techniques and cloud solutions, with a preference for AWS Certified Machine Learning or AWS Certified Solutions Architect credentials.
• Proven experience in managing the delivery of advanced analytics, AI/ML-driven projects.
• Advanced expertise in AWS Sagemaker and its subfeatures, which include SageMaker Pipelines, Feature Store, Model Registry, and others.
• Strong knowledge of Lambda Functions, S3 Buckets, AWS Glue, Redshift, and Kinesis
• Strong knowledge of AWS and Data ETL processes.
• Knowledge to create maintainable deployments of machine learning models
• Intermediate proficiency in Python
• Intermediate proficiency using Anaconda.
• Previous experience with MLOps methodologies and practices.
• Strong knowledge of Microsoft Office
• Familiar with Agile project management and development life cycle.

What We Do

DCU is the largest credit union headquartered in New England – serving more than one million members in all 50 states. With over 1,900 team members, we strive to make DCU a great place to work with an excellent work-life balance, and a community that cares.

DCU is an equal opportunity employer, and we value diversity, inclusion, and equity at our company. We evaluate qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics. 

If you’re applying for a job and need a reasonable accommodation for any part of the employment process, please send an email to careers@dcu.org and let us know the nature of your request and contact information. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to from this email address.

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