Data Scientist — Quality & Pipeline Intelligence

Engai; San Francisco (CA); In loco; USD 150.000 - 230.000; Tempo pieno

Vantaggi offerti da questo lavoro

International health insurance

Dental insurance

Vision insurance

Annual in-person global companyRetreat

Descrizione del lavoro

Engai is seeking a Data Scientist focused on Quality & Pipeline Intelligence to advance active learning and anomaly detection within complex training datasets.

You will work with state-of-the-art foundation models and autonomous systems, validating models through statistical methods and client-facing scorecards.

Competenze

• BS/MS in Data Science, Statistics, Computer Science, or quantitative field.
• Hands-on experience with Python, PyTorch/Scikit-Learn, and statistical hypothesis testing.
• Experience handling unstructured data pipelines (images, audio, LiDAR, or text).
• Background in ML data curation or active learning is a major plus.

Mansioni

• Formulate active learning sampling algorithms prioritizing high-entropy data slices for human review.
• Construct automated anomaly detection scripts identifying label drift and annotation noise.
• Author statistical validation papers and performance scorecards for deployments.
• Partner with platform engineers to productionize data validation pipelines.

Conoscenze

Active learning

Hypothesis testing

Unstructured data handling

Formazione

BS or MS in Data Science, Statistics, CS, or quantitative discipline

Strumenti

Python

PyTorch

Scikit-Learn

Descrizione del lavoro

Data Scientist — Quality & Pipeline Intelligence

Develop algorithmic active learning data selection algorithms, model uncertainty filters, and anomaly detection models for complex training datasets.

Responsibilities

• Formulate active learning sampling algorithms that prioritize high-entropy data slices for human review
• Construct automated anomaly detection scripts identifying label drift, annotation noise, and guideline deviation
• Author statistical validation papers and client-facing performance scorecards for production deployments
• Partner closely with platform engineers to productionize data validation pipelines

Requirements

• B.S. or M.S. in Data Science, Statistics, Computer Science, or quantitative discipline
• Hands-on experience with Python, PyTorch / Scikit-Learn, and statistical hypothesis testing
• Experience handling unstructured data pipelines (images, audio, LiDAR point clouds, or text)
• Prior background in machine learning data curation or active learning is a major plus
• Top-of-market base salary and equity package
• Work with state-of-the-art foundation models and autonomous systems
• Comprehensive international health, dental, and vision insurance
• Annual in-person global company retreats

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