Sesame

Data Engineer, Machine Learning

San Francisco · Contract

Sponsorship not specifiedDetected 29 days ago

PythonSQLVector DatabasesKubernetesMachine LearningAirflowData EngineeringAI OrchestrationCompensationEmbedded SystemsCommunication

About the role

Sesame's data is rich and complex: conversations, voice, sensor signals, and product telemetry.
This is a deeply technical, infrastructure-focused role - closer to ML engineering than traditional data analytics.

Design and build production data pipelines that prepare conversational, voice, and multimodal data for model training and evaluation.
Partner directly with ML engineers to understand data requirements for new models and experiments, and deliver datasets that meet those needs.
Build and maintain infrastructure for dataset versioning, lineage tracking, and reproducibility - so any training run can be traced back to its exact data.
Build tooling that makes it easy for ML engineers and researchers to discover, explore, and request data independently.
You'll design the systems that take raw, unstructured, multimodal data and turn it into clean, versioned, well-documented datasets that ML teams can trust and build on confidently.
You'll be deeply embedded with ML teams, understanding their workflows and building infrastructure that accelerates the full model development lifecycle - from data collection and labeling through training and evaluation.
Sesame believes in a future where computers are lifelike - with the ability to see, hear, and collaborate with us in ways that feel natural and human.

5+ years in data engineering, with meaningful experience supporting ML or AI teams specifically.
Experience with workflow orchestration systems such as Airflow, Dagster, or Prefect.
Hands-on experience with ML data workflows: training data pipelines, dataset versioning, data labeling pipelines, or model evaluation data.
Comfort working with unstructured and semi-structured data - audio, text, JSON logs - not just clean relational tables.

Vector databases, embedding storage, or feature stores.
Data from hardware or embedded systems: telemetry, sensors, real-time streams.
Sesame is committed to a workplace where everyone feels valued, respected, and empowered.
We welcome all qualified applicants, embracing diversity in race, gender, identity, orientation, ability, and more.
We provide reasonable accommodations for applicants with disabilities.
Contact careers@sesame.com for assistance.
401 (k) max employer match: 3.5% of compensation

Distributed compute frameworks for large-scale data processing such as Ray or Spark.
Kubernetes and managed Kubernetes environments such as GKE or EKS.
Data privacy frameworks, especially around voice or conversational data.
Building internal tooling or self-serve data platforms.

100% employer-paid health, vision, and dental benefits for you and your dependents
Unlimited PTO and sick time
Flexible spending account with employer matching up to $1,650/year (medical FSA)
Opportunity to share in the company's success with competitive stock options
Benefits do not apply to contingent/contract workers.
With this vision, we're designing a new kind of computer, focused on making voice agents part of our daily lives.
Develop data quality frameworks that catch issues before they become model quality issues: schema validation, drift detection, and coverage monitoring.
You'll collaborate directly with machine learning engineers and researchers - your job is to make sure they have the right data, in the right shape, at the right time to train, evaluate, and ship models.

We're looking for a Data Engineer to build and maintain the data pipelines that feed Sesame's AI models.

This listing is sourced directly from Sesame's careers page and normalized into a canonical job model.