Senior Machine Learning Engineer

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