Machine Learning Engineer

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 prioritize learning and teamwork and love giving people the opportunity to champion big challenges and grow into better versions of themselves.

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

• 3+ 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