Data & Applied Machine Learning Engineer

Overview

Data and Applied Machine Learning Engineer — Irvine, CA

Location: Irvine, CA

Schedule: Onsite (hybrid schedule similar to engineering team norms)

Employment Type: Full Time, Permanent

Compensation: 150,000 to 175,000 base plus 5 percent AIP bonus

A growing engineering organization in Irvine is seeking a Data and Applied Machine Learning Engineer to join a collaborative, cross functional team. This position combines high level data engineering with applied ML ownership and offers the chance to work closely with a recently acquired AI division focused on computer vision and machine learning.

This role is a backfill that has evolved from a traditional data engineering position into a hybrid data and ML role with end to end ownership of pipelines, modeling workflows, and data quality for production systems.

Data Platform, Pipelines, and Quality (Primary Focus)

• Design, build, and operate scalable ELT and ETL pipelines ingesting data from IoT devices, smart cart telemetry, video events, operational systems, and external partners
• Build and maintain cloud based data infrastructure including SQL and No
  
  SQL databases, data warehouses, and integration systems
• Create and maintain canonical data models including schemas, taxonomies, KPIs, and event structures
• Implement robust data quality practices including validation rules, automated tests, anomaly detection, monitoring, and alerting
• Improve consistency across data producing systems through naming standards, identifiers, timestamps, joins, and deduplication
• Perform root cause analysis on pipeline issues and implement durable, long term fixes
• Partner with BI and Product teams to build curated datasets, semantic layers, and internal dashboards for visibility into system health

Applied Machine Learning Ownership (Secondary Focus)

• Own the end to end production lifecycle of a smart cart classification model including data collection, labeling, evaluation, threshold tuning, and safe deployment
• Build and optimize ML pipelines for feature engineering, model training, deployment, and monitoring in production
• Create and maintain evaluation frameworks including repeatable test sets and offline metrics
• Monitor model performance for accuracy drift, data drift, and classification error patterns
• Collaborate with a separate ML team to incorporate model improvements while maintaining stability in production environments
• Work closely with software and systems engineers to integrate the classifier cleanly into product workflows with strong telemetry, logging, and operational documentation

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Mathematics, Statistics, or related field
• 5 plus years of experience in data engineering or ML engineering
• Strong fluency in SQL and Python
• Proven experience building and operating production ELT and ETL pipelines
• Experience with cloud platforms Azure or GCP
• Hands on experience with orchestration or transformation tools such as Airflow or Prefect
• Experience with Spark, Databricks, or similar batch processing frameworks
• Strong understanding of data modeling, governance, quality practices, and lineage
• Ability to troubleshoot data issues, collaborate with operations teams, and implement production ready solutions
• Strong analytical communication and problem solving abilities
• Must be a US Citizen or Green Card holder

• Proactive and comfortable working autonomously
• Communicative and collaborative across engineering, product, and analytics teams
• Analytical mindset with a focus on delivering clear business insights
• Standard benefits package including medical, dental, PTO, and a 5 percent annual incentive bonus

Equal Opportunity Employer/Veterans/Disabled

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The Company will consider qualified applicants with arrest and conviction records in accordance with federal, state, and local laws and/or security clearance requirements, including, as applicable:

• The California Fair Chance Act
• Los Angeles City Fair Chance Ordinance
• Los Angeles County Fair Chance Ordinance for Employers