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 (ML) engineer with experience and passion for the creation and operationalization of natural language processing (NLP) machine learning models. We seek an individual who can leverage unstructured data, apply NLP and other ML techniques to deliver insights and solve real world business problems for our customers.
Job Responsibilities
- Producing production-level code for training and deploying ML models.
- Contributing to end-to-end ML development pipeline design and utilizing pipeline to design, train, test and deploy ML models.
- Designing and implementing models meeting business requirements and iterating on functionality to provide the best models for production.
- Working in an Agile environment to research and implement best techniques and apply ML to complex problems
Must Haves
- Master’s or PhD degree in Computer Science, Mathematics, or equivalent
- 4+ years’ experience as Machine Learning Engineer working with production code
- 2+ years’ experience with machine learning cloud platforms (Amazon, Azure, Google, IBM)
- 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
- Experience with Natural Language Processing (NLP) models
- Knowledge of fine tuning pre-trained models (BERT)
- 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.