AdTechTalent
Data Science2 months agoHybrid

DoubleVerify

Manager, Data Science & Research

machine learningdeep learningcomputer visionNLPmultimodalPyTorchTensorFlowscikit-learnOpenCVHuggingFaceLLMsembeddingsfoundation modelsAutoMLactive learningdata-centric AIdata scienceleadershipmodel deploymentautomation

Key details

Salary

Not specified

Employment type

Full-time

Seniority

Lead

Years experience

5-10

Location

Tel Aviv, Israel

Full job description

Lead a team of experienced Data Scientists with ~70% hands-on involvement. Work on large-scale core systems with scarce labels and strict latency/cost constraints. Responsibilities include developing content classification systems for social platforms, web, and apps; designing models in computer vision, NLP, and multimodal pipelines; managing full ML lifecycle from data selection to deployment; developing data curation and labeling strategies; improving model precision/recall balancing cost and latency; driving automation systems; applying modern AI approaches including LLMs and foundation models; mentoring senior Data Scientists; collaborating with ML Engineering, Product, and Policy teams. Requirements: 3+ years leading Data Science/ML teams, 6+ years hands-on ML/DL experience, strong background in Computer Vision and/or NLP, experience deploying production ML systems at scale, understanding of trade-offs in accuracy, cost, latency, hands-on with PyTorch/TensorFlow, ML/DS tools like scikit-learn, OpenCV, HuggingFace, experience with large datasets and evaluation pipelines. Advantages include experience with multimodal systems, LLMs, embeddings, foundation models, AutoML, active learning, and data-centric AI. Role is full-time, hybrid, located in Tel Aviv, Israel.

What you'll do

  • Lead development of content classification systems across social platforms (Meta, TikTok, YouTube), web, and apps
  • Design and build models across computer vision, NLP, and multimodal pipelines
  • Own the full lifecycle: data selection -> labeling strategy -> training -> evaluation -> deployment
  • Develop strategies for efficient data curation and labeling (active learning, auto-labeling, sampling under scale)
  • Improve model quality (precision/recall) while balancing cost, latency, and scale
  • Drive automation systems (auto-labeling, auto-curation, retraining loops)
  • Apply modern AI approaches (LLMs, embeddings, foundation models) to real production problems
  • Lead and mentor a team of senior Data Scientists, setting technical direction and pushing execution forward
  • Work closely with ML Engineering, Product, and Policy to translate ambiguous requirements into scalable systems

Requirements

  • 3+ years of experience leading Data Science / ML teams
  • 6+ years of hands-on experience in Machine Learning / Deep Learning
  • Strong background in Computer Vision and/or NLP
  • Experience building and deploying production ML systems at scale
  • Strong understanding of real-world trade-offs (accuracy, cost, latency)
  • Hands-on experience with deep learning frameworks (PyTorch / TensorFlow)
  • Experience with ML/DS tools (scikit-learn, OpenCV, HuggingFace, etc.)
  • Experience working with large datasets and model evaluation pipelines

Tech stack

PyTorchTensorFlowscikit-learnOpenCVHuggingFaceLLMsembeddingsfoundation modelsAutoMLactive learningdata-centric AI

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