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Staff Machine Learning Engineer

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Staff Machine Learning Engineer in USA

  • Remote

Responsibilities

  • Define the technical direction and multi-year roadmap for ads retrieval modeling.
  • Design, develop, and launch candidate-generation and retrieval models for campaigns and ads.
  • Apply representation learning, embeddings, sequence models, graph-based methods, two-tower architectures, and deep learning techniques.
  • Improve objectives, labels, sampling strategies, hard-negative mining, feature design, embedding generation, candidate filtering, and retrieval depth.
  • Work with approximate nearest-neighbor and vector retrieval systems while balancing recall, relevance, freshness, diversity, coverage, latency, and cost.
  • Establish evaluation practices connecting retrieval metrics to downstream advertising and user outcomes.
  • Lead offline analysis and online experiments and translate results into subsequent modeling iterations.
  • Partner with ranking, ads platform, auction, measurement, and product teams to integrate retrieval models into the ads funnel.
  • Write design documents, review code and model changes, and improve modeling, testing, observability, and production ownership.
  • Mentor ML engineers and develop team expertise in retrieval, recommendation, and representation learning.

Requirements

  • At least 7 years of industry experience, including substantial experience building and shipping applied ML products.
  • Deep experience with information retrieval, candidate generation, recommender systems, ranking, or related relevance problems.
  • Strong understanding of DNNs, embeddings, two-tower or dual-encoder models, approximate nearest-neighbor search, and multi-stage retrieval.
  • Deep experience training, evaluating, debugging, and deploying deep learning models with TensorFlow, PyTorch, or similar frameworks.
  • Experience owning ML projects from problem framing and data preparation through offline evaluation, online experimentation, production launch, and iteration.
  • Strong command of experimental design and model evaluation, including relationships between offline retrieval metrics and downstream business and user metrics.
  • Experience with large-scale behavioral, contextual, or content datasets and complex feature pipelines.
  • Strong software engineering fundamentals and ability to write reliable, maintainable production code.
  • Technical leadership experience setting direction, leading complex projects, influencing partner teams, and mentoring engineers.
  • Excellent written and verbal communication skills.
  • Preferred: experience with ads retrieval, ads ranking, ad targeting, ad serving, recommendation, search relevance, or marketplace optimization.
  • Preferred: experience modeling user, content, campaign, or ad interactions with sequential, graph, or multimodal signals.
  • Preferred: experience connecting retrieval improvements to ranking, auction, conversion, revenue, or user-experience outcomes.
  • Preferred: experience in ads marketplaces, publications, patents, industry contributions, or sequential modeling with RNNs or Transformers.

Benefits

  • 100% remote opportunity, with four office locations in New York, San Francisco, Los Angeles, and Chicago for hybrid or onsite work preferences.
  • Comprehensive healthcare benefits and income replacement programs.
  • 401(k) with employer match.
  • Global benefits supporting workspace, professional development, and caregiving.
  • Family planning support.
  • Gender-affirming care.
  • Mental health and coaching benefits.
  • Flexible vacation and paid volunteer time off.
  • Generous paid parental leave.
  • The position may be eligible for equity and, depending on the position offered, commission.

Salary: $230k - $322k/yr

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