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Senior Manager, Machine Learning Search

Posted about 1 month agoViewed

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💎 Seniority level: Manager, 8+ years

📍 Location: United States

💸 Salary: 195000.0 - 308000.0 USD per year

🔍 Industry: Software Development

🏢 Company: Upwork👥 501-1000💰 over 8 years ago🫂 Last layoff almost 2 years agoMarketplaceFreelanceCopywritingPeer to Peer

🗣️ Languages: English

⏳ Experience: 8+ years

🪄 Skills: AWSBackend DevelopmentPythonCloud ComputingGCPKubernetesMachine LearningMLFlowAlgorithmsAzureData scienceData StructuresREST APISparkSoftware EngineeringA/B testing

Requirements:
  • 8+ years of experience in software engineering, with at least 3+ years leading ML teams.
  • Strong expertise in machine learning, deep learning, information retrieval, and search technologies.
  • Proven experience in search ranking, query understanding, and NLP-based search improvements.
  • Proficiency in distributed computing frameworks (e.g., Spark, Kubernetes).
  • Deep knowledge of deploying scalable ML models in production search systems.
  • Exceptional leadership skills with a track record of building and mentoring high-performing engineering teams.
  • Experience with cloud-based ML infrastructure (AWS, GCP, or Azure).
  • Strong collaboration skills with the ability to drive alignment across product, engineering, and data teams.
Responsibilities:
  • Lead, mentor, and grow a high-performing team of machine learning engineers, data scientists, and backend engineers.
  • Drive the development and deployment of state-of-the-art ML models for search retrieval, ranking, and personalization.
  • Pioneer the integration of Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) into traditional search systems.
  • Collaborate with product, engineering, and data teams to enhance Upwork’s search ecosystem.
  • Establish technical direction and best practices for ML model training, experimentation, and large-scale deployment.
  • Optimize search algorithms to improve user experience, engagement, and conversion rates.
  • Foster an experimentation-driven culture, leveraging A/B testing and data insights to refine search and ranking strategies.
  • Ensure model explainability, fairness, and ethical AI considerations in search algorithms.
  • Develop a roadmap for scaling ML-powered search and stay ahead of industry trends.
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