Machine Learning Engineer at Auror, using data science to reduce retail crime through innovative ML systems. Collaborate with product teams and develop impactful solutions leveraging real - time data.
About the role
- Senior Data and ML Engineer focusing on developing and implementing robust Data Engineering and Machine Learning Operations at Corebridge Financial. Lead design and maintenance of MLops pipelines using AWS SageMaker and other cutting-edge technologies.
Responsibilities
- Lead the design, Build, and maintenance of end-to-end automated MLops pipelines for continuous testing, training and deployment of ML models.
- Optimize AI/ML workloads and build scalable systems using a variety of AWS services, including Amazon SageMaker (for model development, training, and deployment), Amazon Bedrock (for integrating generative AI and large language models), S3, Lambda, and others.
- Collaborate with data scientists and data engineers to design and implement ETL/ELT processes to structure and format data into suitable data warehouses or data lakes for analysis and model training.
- Implement comprehensive monitoring, logging, and alerting for production AI/ML systems to track performance, resource utilization, error rates, and troubleshoot issues as they arise.
- Work closely with cross-functional teams, including data scientists, Data engineers, and business analysts, to translate business requirements into technical solutions. Ensure adherence to data governance, security, and compliance principles.
Requirements
- Bachelor’s or Master's degree in Computer Science, Engineering, Data science, or a related technical field.
- 15+ years of IT experience with 10+ years of experience in Data Engineering, ML engineering, or MLOps role.
- Proven experience using cloud technologies, with significant hands-on experience in AWS Data & AI services and Snowflake Data platform.
- Strong background and experience in leveraging MLOps platforms (MLflow, Kubeflow, Sagemaker) and ML CI/CD workflows to manage the ML lifecycle.
- Proficiency in programming languages like Python or PySpark.
- Strong Hands on experience with Amazon SageMaker for ML and Amazon Bedrock for generative AI solutions.
- Hands-on experience with ETL/ELT frameworks (e.g., Apache NiFi, Airflow, Talend, dbt, AWS Glue)
- Expertise in big data technologies (e.g., Hadoop, Spark, Kafka, Databricks) and Cloud data warehouses (Snowflake, Redshift, BigQuery)
- Strong problem-solving abilities and a passion for working with cutting-edge technologies.
- Excellent communication and collaboration skills to effectively work within a cross-functional team.
Benefits
- Health and Wellness: We offer a range of medical, dental and vision insurance plans, as well as mental health support and wellness initiatives to promote overall well-being.
- Retirement Savings: We offer retirement benefits options, which vary by location. In the U.S., our competitive 401(k) Plan offers a generous dollar-for-dollar Company matching contribution of up to 6% of eligible pay and a Company contribution equal to 3% of eligible pay (subject to annual IRS limits and Plan terms). These Company contributions vest immediately.
- Employee Assistance Program: Confidential counseling services and resources are available to all employees.
- Matching charitable donations: Corebridge matches donations to tax-exempt organizations 1:1, up to $5,000.
- Volunteer Time Off: Employees may use up to 16 volunteer hours annually to support activities that enhance and serve communities where employees live and work.
- Paid Time Off: Eligible employees start off with at least 24 Paid Time Off (PTO) days so they can take time off for themselves and their families when they need it.
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