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Percepta

Cloud-based video analytics for shoplifting detection

Founding Applied AI Engineer - Data

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • Strong experience in some combination of data science, data engineering, and machine learning.
  • Comfort designing systems that reconcile real-time streaming data and batch or warehouse data under real latency constraints.
  • Fluency reading and questioning machine-learning model evaluation metrics, including AUC, precision and recall, and confusion matrices, to assess whether models will hold up in production.
  • Demonstrated instinct for data skepticism, including questioning whether clean-looking numbers are correct and investigating raw records rather than relying on aggregates.
  • Fluency using AI-assisted coding tools as a primary workflow, with the judgment to verify and defend one's own analysis independently.
  • Product instinct and interest in building tools that make data work easier, not only performing the work.
  • Intuition for the data needs of modern AI, machine-learning, and large language model systems, including features, retrieval, context, and embeddings.
  • Comfort working directly with customer teams; high ownership and strong communication.

Responsibilities

  • Turn high-value use cases from ideas into production by working directly with customer operators and engineers to drive transformation through data and AI.
  • Own the full lifecycle of production models, including featurizing data, establishing serving pipelines, and building retraining and monitoring loops.
  • Build end-to-end pipelines across streaming and batch sources to transform fragmented enterprise data into AI-ready assets.
  • Integrate large language models into production pipelines, such as for structured extraction from unstructured clinical notes, and own prompt quality and output reliability evaluation.
  • Build internal products and tooling that make data work faster and repeatable across customers.
  • Form and communicate technical opinions about data models, storage, orchestration, and infrastructure tradeoffs.

Desired Qualifications

  • Experience building agentic or automated data-engineering tooling.
  • Hands-on experience with modern cloud data platforms such as Databricks and streaming systems such as Kafka.
  • Experience with health-system data, including electronic health records, claims, admission-discharge-transfer feeds, and other operational healthcare datasets, or other complex regulated enterprise data.
  • Experience using a large language model as a structured-extraction step inside a larger data pipeline rather than only as a chat interface.
  • Prior startup, founding, or forward-deployed experience.

About the Company

Percepta

Cloud-based video analytics for shoplifting detection

Percepta Labs builds cloud-based video analytics for retail loss prevention. It ingests retailers’ existing security camera feeds and uses action recognition and pose estimation to identify behaviors that could indicate shoplifting in real time, then assigns a probability that a theft is happening. The system emphasizes ethical AI by anonymizing demographic features (race, gender, age) to avoid bias and protect privacy. The product is sold to retailers to help reduce shrinkage and improve margins, with early testing claiming higher accuracy than human loss-prevention staff. Percepta’s growth has been supported by a major investment from ADT Commercial, which acquired the company and appointed its co-founder as ADT’s first Director of Artificial Intelligence. The company’s goal is to provide scalable, privacy-conscious video analytics that help retailers prevent theft more efficiently and cost-effectively.

Company size
1-10
Company stage
Seed
Total funding
$1M
Headquarters
New York City, New York
Founded
2019

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