About the job Deep Learning Engineer
We are looking for a Deep Learning Engineer to join our growing Research and Development team. This is a unique opportunity where you will get a chance to work with established and rapidly evolving platforms that handle millions of requests and massive amounts of events, and other data. In this position, you will be responsible for taking on new initiatives to automate, enhance, maintain, and scale services in a rapidly-scaling environment.
As a member of our team, you will make an immediate impact as you help build out and expand our technology platforms across several software products. This is a fast-paced role with high growth, visibility, impact, and where many of the decisions for new projects will be driven by you and your team from inception through production.
About the position and responsibilities
The ideal candidate is an experienced Deep Learning Engineer and can serve as a leader on the team for organizing structured and unstructured data, helping to work with the team to create data pipelines, updating existing models, and experimenting with new optimizations. Our data provides the best understanding of user behavior, that needs daily updates and availability across many countries.
Along with a supporting cast of data engineers and application developers, the Deep Learning Engineer will create new models, systems & tools to help provide answers that allow our customers to continue to build out a large single-source set of data across from multiple channels.
What we are looking for
• Strong background in the foundations of deep learning with a proven track record of productionalization of models for NLP, computer vision, information extraction, or related practice
• Expertise with at least one deep learning framework (PyTorch, TensorFlow, or equivalent)
• Knowledge in the latest NLP-related algorithms and methods such as transformers, sequence-to-sequence models, word and sentence embeddings, attention, etc
• Fluency in Python
• Familiar with SQL
• Experienced Software Engineering and Data Modeling fundamentals
• A Masters or PhD in Computer Science, Mathematics, Statistics, or another quantitative discipline or 3+ years equivalent industry experience
Extra Nice to Haves
• Familiar with containerization and deployment (Docker, Kubernetes)
• Experience with C++
• Demonstrated ability to drive selection of machine learning approaches to solve specific problems coupled with the ability to clearly communicate tradeoffs
• Experience working with a MPP data warehouse (aka Redshift, Snowflake)
• Experience configuring and optimizing data pipelines
• Experience in Marketing Analytics field
• Experience on AWS Sagemaker
• General software design patterns (REST, MVC, Auto-scaling, etc.)
• Experience with ML models leveraging reinforcement learning