4 days ago
Base Salary
$195k - $343k/yr
Responsibilities
- Lead the design and development of machine learning models for Search ranking, including relevance, personalization, result quality, intent understanding, and engagement optimization.
- Own ranking initiatives from problem definition through experimentation, launch, and iteration.
- Develop learning-to-rank, deep retrieval, neural ranking, sequence, embedding, multi-task learning, calibrated prediction, and large-scale feature engineering solutions.
- Build ranking systems that balance relevance, satisfaction, freshness, diversity, fairness, safety, latency, and business goals.
- Define success metrics, experimentation strategies, and long-term ranking roadmaps with product managers, data scientists, and engineers.
- Analyze user behavior, search logs, query-result interactions, and model performance to identify improvements.
- Design offline evaluation, online experimentation, and model monitoring frameworks.
- Improve feature pipelines, training infrastructure, serving systems, and ML model iteration velocity.
- Provide technical leadership across teams, influence architecture decisions, and mentor engineers.
Requirements
- Bachelor’s degree in a relevant technical field such as computer science, or equivalent years of practical work experience.
- 8+ years of post-bachelor’s machine learning experience, or a master’s degree plus 7+ years of post-graduate ML experience, or a PhD plus 4 years of post-graduate ML experience.
- Experience developing machine learning models for relevance ranking, personalization, intent understanding, and/or engagement optimization.
- Strong machine learning fundamentals in supervised learning, ranking models, embeddings, deep learning, optimization, evaluation, and experimentation.
- Strong programming skills in Python, C++, Java, Scala, or similar languages.
- Experience with large-scale data processing and ML infrastructure such as Spark, Flink, Beam, TensorFlow, PyTorch, JAX, or similar tools.
- Experience taking ML models from research or prototyping into large-scale production systems.
- Strong understanding of online experimentation, A/B testing, metric design, model debugging, and tradeoff analysis.
- Proven ability to lead complex technical projects across multiple teams and communicate complex ML concepts to technical and non-technical stakeholders.
- Preferred qualifications include an advanced degree; Search, ads, recommendation, feed, marketplace, or content discovery ranking experience; learning-to-rank and transformer-based ranker experience; retrieval, ANN search, embeddings, vector search, or two-stage ranking experience; multi-objective ranking optimization; LLM, foundation model, semantic search, natural language understanding, or retrieval-augmented generation experience; low-latency ML serving and reliability experience; and publications, patents, or other advances in applied ML.
Benefits
- Paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages including long-term equity participation through RSUs.
- Default-together work arrangement requiring employees to work in an office 4+ days per week.
- Position is offered in U.S. pay zones with location-dependent base salary ranges.
Tech Stack
Categories
About Snap
Snap Inc. builds Snapchat, a visual messaging app, and supports augmented reality through Lens Studio and Spectacles, plus related services like Bitmoji. The company monetizes primarily via advertising and sponsored AR experiences for consumers, creators, and brands. Founded in 2011 and headquartered in Santa Monica, it is publicly traded on the NYSE under the ticker SNAP.