Senior Data & ML Engineer, MLOps

Overview

Who We Are

At Corebridge Financial, we believe action is everything. That’s why every day we partner with financial professionals and institutions to make it possible for more people to take action in their financial lives, for today and tomorrow. We Align To a Set Of Values That Are The Core Pillars That Define Our Culture And Help Bring Our Brand Purpose To Life:

• We are stronger as one:
  We collaborate across the enterprise, scale what works and act decisively for our customers and partners.
• We deliver on commitments:
  We are accountable, empower each other and go above and beyond for our stakeholders.
• We learn, improve and innovate:
  We get better each day by challenging the status quo and equipping ourselves for the future.
• We are inclusive:
  We embrace different perspectives, enabling our colleagues to make an impact and bring their whole selves to work.

Who You’ll Work With

The Information Technology organization is the technological foundation of our business and works in collaboration with our partners from across the company. The team drives technology and digital transformation, partners with business leaders to design and execute new strategies through IT and operations services and ensures the necessary IT risk management and security measures are in place and aligned with enterprise architecture standards and principles.

We are seeking a highly skilled and motivated Senior Data and ML Engineer with a strong focus on MLOps to join our Data Platform Engineering team, focusing on developing and implementing robust Data Engineering and Machine Learning Operations (MLOps) practices. In this role, you will play a critical part in designing, building, and maintaining scalable and reliable infrastructure for the entire machine learning and GenAI lifecycle, from experimentation to production deployment and monitoring.

You will work with cutting-edge cloud technologies, specifically leveraging the power of AWS Sage Maker, Amazon Bedrock, and Snowflake Data Platform to drive innovation in the financial services sector.

• Design and Implement ML Pipelines:
  Lead the design, build, and maintenance of end-to-end automated MLOps pipelines for continuous testing, training, and deployment of ML models.
• Optimize ML workloads:
  Optimize AI/ML workloads and build scalable systems using AWS services including Sage Maker (model development, training, deployment), Bedrock (generative AI and LLMs), S3, Lambda, and others.
• Manage Data Integration:
  Collaborate with data scientists and data engineers to design and implement ETL/ELT processes to structure data into suitable data warehouses or data lakes for analysis and model training.
• Monitoring and Maintenance:
  Implement comprehensive monitoring, logging, and alerting for production AI/ML systems to track performance, resource utilization, error rates, and troubleshoot issues.
• Collaboration & Governance:
  Work with cross-functional teams to translate business requirements into technical solutions. Ensure adherence to data governance, security, and compliance principles.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related technical field.
• 15+ years of IT experience with 10+ years in Data Engineering, ML engineering, or MLOps.
• Proven experience with cloud technologies, especially AWS Data & AI services and Snowflake Data Platform.
• Strong background in leveraging MLOps platforms (MLflow, Kubeflow, Sage Maker) and ML CI/CD workflows.
• Proficiency in programming languages like Python or PySpark.
• Hands-on experience with Amazon Sage Maker for ML and Amazon Bedrock for generative AI solutions.
• Experience with ETL/ELT frameworks (e.g., Apache NiFi, Airflow, Talend, dbt, AWS Glue).
• Expertise in big data technologies (Hadoop, Spark, Kafka, Databricks) and cloud data warehouses (Snowflake, Redshift, Big Query).
• Strong problem-solving abilities and a passion for cutting-edge technologies.
• Excellent communication and collaboration skills to work effectively within cross-functional teams.

The anticipated salary range for this position is $135,000 to $190,000 at the commencement of…