Machine Learning Research Scientist
- Location: Belllevue, WA
- Job Number: 7065820
- Posting Date: Apr 20, 2020
- Application Deadline: Open Until Filled
Job DescriptionCognitiv builds state-of-the-art machine learning systems for bidding into real-time programmatic advertising marketplaces. Our platform is designed from the ground up to be a scalable high-performance system for deploying deep learning technology. It enables us to train custom neural network models that drive measurable return on advertising investment for each of our clients.
We are looking for exceptional independent collaboration-minded experts in machine learning to bring innovative ideas to our Research and Development Team. The team is focused on incorporating the latest advances in deep learning into our products, but we are open to any new methods capable of efficient and effective learning that drives the performance of our products. Come join us in the Bay Area or at our new Bellevue, WA office located near Seattle! We offer compelling employment opportunities with competitive salaries, stock options and a robust benefits package.
Build machine learning models by designing data sets, objective functions, architectures, and training schemes.
Design and execute well-controlled experiments to assess the performance of model designs.
Apply statistical methods for assessing significance.
Provide clear and compelling presentation of results.
Solve problems and answer questions involving large complex datasets.
Ability to understand and implement ideas in academic machine learning literature.
Work with machine learning engineers to implement developments and improve internal tools and processes.
PHD (must be completed).
3 Years Industry experience.
3 Years demonstrated PM experience ( Possess the ability to drive a research project forward).
Demonstrated record of coming up with innovative ideas or improving existing ideas in machine learning.
Proficiency within Python, including core data science frameworks - NumPy, SciPy, panda, Jupyter, etc.
Academic or professional experience with Deep Learning framework (MXNet, TensorFlow, PyTorch, etc).
Expert proficiency in relevant programming languages (e.g. Python, Scala, Java).
Cloud experience (AWS, Azure, GCE).
Experience with SQL/NoSQL (postgres, presto, cassandra, etc)
Experience applying statistical methods.
Expertise in Recurrent Neural Networks
Expertise in Deep Reinforcement Learning
Expertise in Optimization
Expertise in Natural Language Processing