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Senior Machine Learning Engineer en Raya

Raya · Los Angeles or Remote, Estados Unidos De América · Remote

Python

Kubernetes Container Platforms

Microsoft Excel

Software Engineer

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Description

We prioritize learning and teamwork and love giving people the opportunity to champion big challenges and grow into better versions of themselves. A great candidate is excited to grow our use of machine learning, AI, and other sophisticated algorithms to build a better user experience. Finally, they believe in Raya’s vision, which is to enrich lives by fostering relationships through quality, in person interactions.

We offer comprehensive medical and dental coverage, $50 a day food delivery budget, equity based employment, a great culture, learning opportunities, unlimited vacation, 12 weeks paid parental leave, and we pay all employees $1,000 a year to go somewhere in the world that they’ve never been because of our values of human connection, empathy, and curiosity.

Responsibilities

  • Design and implement machine learning models to power highly personalized experiences throughout the Raya app 
  • Work in a high-impact environment with rapid development and product iteration
  • Contribute to core ML platform components for scalable model training, deployment, and productionization
  • Collaborate closely with cross functional stakeholders in data science, product management, and other engineering teams to shape roadmaps and initiatives
  • Stay up-to-date with the latest research and advancements in recommendation systems and AI

    • Qualifications

  • 5+ years of experience in machine learning, recommendations/ranking systems, computer vision, multimodal representation learning, and/or natural language processing
  • Proven track record of delivering machine learning models with business impact and shipping ML solutions to production
  • Strong background in Python programming and ML frameworks like PyTorch, TensorFlow, Transformers, etc.
  • Proficiency with ML platforms and tools for model experimentation, deployment, and monitoring
  • Well-versed in software engineering design patterns, principles, architectures, and operations
  • Experience with data processing at scale, including batch/streaming pipelines and data infrastructure tools like Kubernetes, Kafka, and Spark
  • Excellent verbal and written communication skills with the ability to communicate complex topics to technical and non-technical stakeholders

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