ML Data Engineer: Multimodal Data Pipelines + Stock Options

Sesame; Bellevue (WA); On-site; USD 170,000 - 280,000; Full time

Benefits offered by this job

401(k) match

Health, vision, dental coverage

Unlimited PTO

Flexible spending account

EAP

Stock options

Job summary

Sesame is seeking a Data Engineer to build and maintain data pipelines that feed our AI models, working closely with ML engineers and researchers to ensure data is clean, versioned, and ready for training and evaluation.

You will design systems handling multimodal data, including conversations and sensor signals, turning raw data into trusted datasets for model development, with a strong focus on data quality and governance.

Qualifications

• 5+ years in data engineering, with ML/AI support experience.
• Strong SQL and Python skills used daily.
• Experience building and operating ETL/ELT pipelines at scale.
• Experience with workflow orchestration systems (Airflow, Dagster, Prefect).
• Hands-on experience with ML data workflows: training data pipelines, dataset versioning, or eval data.
• Understanding of how ML teams work and data quality impact on models.
• Comfort with unstructured data (audio, text, JSON logs).
• Strong communication to bridge data systems and model needs.

Responsibilities

• Design and build production data pipelines for conversational, voice, and multimodal data used in model training and evaluation.
• Collaborate with ML engineers to define data requirements for new models and experiments.
• Maintain dataset versioning, lineage tracking, and reproducibility for training runs.
• Develop data quality frameworks: schema validation, drift detection, coverage monitoring.
• Optimize large-scale data processing for cost and performance across cloud infra.
• Create tooling for ML engineers to discover, explore, and request data.
• Define data governance and privacy standards for sensitive data.
• Contribute to architecture decisions for Sesame's data platform as volume grows.

Skills

SQL

Python

ETL pipelines

Workflow orchestration

ML data workflows

Data governance

Unstructured data

Communication

Tools

Airflow

Dagster

Prefect

Ray

Spark

Kubernetes

Job description

Sesame is seeking a Data Engineer to build and maintain data pipelines that feed our AI models, working closely with ML engineers and researchers to ensure data is clean, versioned, and ready for training and evaluation.

You will design systems handling multimodal data, including conversations and sensor signals, turning raw data into trusted datasets for model development, with a strong focus on data quality and governance.