What You Will be Doing:

• Build high-quality and scalable systems for deploying AI models
• Design, develop, and lead platform features 
• Collaborate with ML Engineers, Backend Engineers, and Products Managers to deliver new Platform capabilities
• Participate in early customer engagements and PoCs, and use that context to drive new product features
• Review design and code, and make sure what we ship is awesome
• “Create what’s not there”

Prior Experience:

• Bachelor’s degree in computer science or equivalent 
• 5+ years experience in Software Engineering, preferably in data Infrastructure, machine learning, and/or cloud ecosystems
• Experience building data systems or machine learning ecosystems 
• Experience with Machine learning frameworks including sklearn, PyTorch, TensorFlow
• Experience in one or more data stores including Postgres, Redshift, Hadoop, Cassandra, BigQuery, Spark, Druid, etc.
• Familiarity with open-source data & machine learning landscape
• Strong mathematical skills and data manipulation using tools like numpy, pandas, PyTorch, TensorFlow
• Experience in the ML development cycle such as training, testing, monitoring, and/or deployment
• Solid background in the fundamentals of computer science and distributed systems
• Ability to build systems that balance scalability, availability, and latency
• Advocate for the continuous deployment and automation tools, monitoring, and self-healing systems
• Great communication skills and a team player

Nice to haves:

• Experience in containerized deployment or Kubernetes
• Exposure to ML pipeline Kubeflow, mlflow, etc. 
• Having been a part of an engineering team at an early-stage startup