DeepSee.ai represents a new category of people-first automation solutions in the wake of frustration with the widespread failure of AI-powered productivity projects to deliver value. We’ve created the world’s first Knowledge Process Automation (KPA) platform to mine unstructured data, operationalize AI-powered insights, and automate results into real-time action for the enterprise. Taking AI-productivity from the lab and into production, the KPA suite is especially useful in highly regulated industries such as the capital markets and insurance verticals, with a business solution flow architecture designed to automate line-of-business problems leveraging the very latest innovations in semantic modeling and natural language processing, all while solving the deployment, scalability, and availability issues that plague most robotic AI initiatives. In a world where enterprises are swimming in data, but very little insight, DeepSee.ai is putting the power of AI and the advantages of knowledge in the hands of the humans.

DeepSee is seeking a self-driven Machine Learning Architect with experience and a passion for the creation and operationalization of natural language processing (NLP) machine learning pipelines. We seek an individual who has deep experience and expertise with architecting systems based on graph databases, semantic search indexes, and information retrieval/search algorithms.

Job Responsibilities

• Building out cloud infrastructure for complex machine learning pipelines in AWS, Azure, and GCP. 
• Architecting and building out complex and scalable graph databases including AWS Neptune, Neo4j, etc.
• Experience building deep learning models on graph structures and graph representations.
• Deep expertise in data retrieval and deep learning search algorithms (e.g. Haystack, Co-search, re-ranking, metadata filtering, small world graphs, etc.)
• Strong background with managing and provisioning systems based on Infrastructure as Code (IaC)
• Working in an Agile environment to research and implement best techniques

Must Haves

• Master’s or PhD degree in Computer Science, Mathematics, or equivalent
• 4+ years’ experience as Machine Learning Engineer or Architect working with production code
• 4+ years’ experience with machine learning cloud platforms (Amazon, Azure, Google, IBM)
• Experience with AWS Neptune, AppSync, OpenSearch, ElasticSearch kNN
• Experience with Natural Language Processing (NLP) models
• Able to work with sparse datasets and implement engineering and ML solutions
• Understanding of Software Engineering, programming, and deployment in Python and AWS
• Experience with TensorFlow, PyTorch, or similar ML frameworks
• Ability to drive technical decisions for ML pipeline for development, maintenance, and deployment

Nice to Haves

• Knowledge of transformers and other deep learning architectures
• Financial or Insurance technology background

Finally, it is important that you align with our Values.
Knowledge Over Noise
One Team, One Dream
Be a Seeker
Stay Human
Act Boldly
Believe!
Own It

We offer 100% company paid premiums on health, dental and vision insurance, unlimited PTO, remote work, and the chance to work on cutting edge technology with seasoned professionals.