LHH is seeking to hire an Applied ML Engineer responsible for building the data, analytics, and applied ML foundation behind next‑generation smart‑device systems. You will design scalable data pipelines, own data quality and governance, and support production ML models that power real‑time classification and decisioning.

Location: Hybrid in Irvine, CA (4 days a week)

Direct hire, full-time (Client unable to support visa sponsorships, NO C2C)

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.

Qualifications

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:

Base Salary: $150,000-175,000 per year
Full benefits package
Hybrid Work Schedule

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

• San Francisco Fair Chance Ordinance

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