LHH · 4 hours ago
Machine Learning Engineer
Irvine, CA
Full-time
Hybrid
Senior Level
$150K/yr - $175K/yr
5+ years expLHH is seeking to hire an Applied ML Engineer responsible for building the data, analytics, and applied ML foundation behind next‑generation smart‑device systems. The role involves designing scalable data pipelines, ensuring data quality and governance, and supporting production ML models for real‑time classification and decisioning.
Human Resources
No H1B
Responsibilities
Build and operate ELT/ETL pipelines ingesting telemetry, video events, operational data, and external sources into a cloud data platform
Manage and optimize SQL/NoSQL databases, data lakes, and data warehouse environments (primarily GCP)
Develop data models, schemas, metrics, and canonical event structures used across product, BI, and analytics
Implement data quality frameworks, validation rules, anomaly detection, monitoring, and alerting
Establish and maintain data governance, naming standards, identifiers, documentation, and data contracts
Diagnose and resolve pipeline issues through root‑cause analysis, with durable long‑term fixes
Partner with BI to build curated datasets, semantic layers, and self‑service analytics resources
Own the lifecycle of production ML models (e.g., classification models): data collection, labeling workflows, evaluation, tuning, deployment, and rollback
Develop feature engineering, training, and model‑serving pipelines with monitoring for accuracy drift and data drift
Collaborate with ML teams to integrate updated models, features, and improvements while ensuring stability
Work with software engineering to integrate ML outputs into products with strong telemetry, logging, and runbooks
Qualification
Required
5+ years of experience in data engineering, data platforms, or ML‑focused pipeline development
Expert‑level SQL and strong Python for data transformations and automation
Hands‑on experience with cloud platforms (GCP preferred; Azure a plus)
Strong background in ETL/ELT, orchestration tools (Airflow, Prefect), and batch/stream processing (Spark, Databricks, etc.)
Experience building and operating data quality, validation, lineage, and monitoring frameworks
Ability to support operations teams by diagnosing in‑field data and model issues
Bachelor's degree in CS, Engineering, Math/Stats, Information Systems, or related field
Strong communication, cross‑team collaboration, and ability to work with BI, UI, and non‑technical stakeholders
Preferred
Experience with ML pipelines, feature engineering, and production model monitoring
Background with real‑time event data, IoT, or computer vision workloads
Familiarity with data governance, metrics standardization, and cloud‑native MLOps
Benefits
Full benefits package
Hybrid Work Schedule
Company
LHH
At LHH, we believe work should be meaningful, fulfilling, and connected.
10001+ employees
Funding
Current Stage
Late StageLeadership Team
Dave Hilbig
President & CEO, OCM-LHH Utah, Wyoming
Ted Diven, MBA
CEO - OCM / Lee Hecht Harrison (ID, MT, NV)
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