ML Data Engineer - Multimodal AI Pipelines & Datasets

Sesame; New York (NY); On-site; USD 170,000 - 280,000; Full time

Benefits offered by this job

401(k) match

Employer-paid health, vision, dental

Unlimited PTO

FSA with employer match

EAP

Stock options

Job summary

Sesame is hiring a Data Engineer to design and maintain data pipelines for its AI models. You will work closely with ML engineers to ensure clean, versioned, and well-documented datasets for training, evaluation, and deployment.

The role is deeply technical and infrastructure-focused, embedding with ML teams to accelerate the full model development lifecycle from data collection and labeling through training and evaluation.

Qualifications

• 5+ years in data engineering, with meaningful experience supporting ML or AI teams specifically.
• Strong SQL and Python skills — you'll use both daily.
• Experience building and operating ETL/ELT pipelines at scale using modern data platforms and tooling.
• 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.
• A solid understanding of how ML teams work and what makes a good training dataset.

Responsibilities

• 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.
• Develop data quality frameworks that catch issues before they become model quality issues: schema validation, drift detection, and coverage monitoring.
• Optimise large-scale data processing for cost and performance across Sesame's cloud infrastructure.
• Build tooling that makes it easy for ML engineers and researchers to discover, explore, and request data independently.
• Define and enforce data governance and privacy standards, particularly around sensitive conversational and voice data.
• Contribute to architecture decisions around Sesame's broader data platform as the team and data volume grow.

Skills

Data engineering

SQL

Python

ML data workflows

Unstructured data

Tools

Airflow

Dagster

Prefect

Spark

Kubernetes

Job description

Sesame is hiring a Data Engineer to design and maintain data pipelines for its AI models. You will work closely with ML engineers to ensure clean, versioned, and well-documented datasets for training, evaluation, and deployment.

The role is deeply technical and infrastructure-focused, embedding with ML teams to accelerate the full model development lifecycle from data collection and labeling through training and evaluation.