Overview
Are you passionate about large scale machine learning? Are you interested in large language models? We are looking for a Principal Applied Scientist who is a team contributor and will work on developing cutting-edge solutions for various document understanding tasks.
Document Understanding plays an important role in understanding various information needs of users and building next generation models to stay ahead of the curve.
In this role, you will be leading projects from idea creation through implementation, experimentation and delivering improvements to real world scenarios, working closely with various partners and customers. We are looking for a passionate and motivated team member who has solid, hands-on experience in transforming business problems into ML problems, collecting high-quality labels, and developing state-of-the-art models to address product challenges and drive value for end users. You will also leverage your software engineering skills and machine learning (ML) expertise in fields such as natural language processing and information retrieval to help create the next generation of text representation.
Responsibilities
- Lead innovation and development of deep learning models for document understanding and their usage in downstream tasks, e.g., Copilot, Generative Search, QA and recommendation, etc.
- Push the state-of-the-art in those areas through multiple aspects, for example:
- Defining the problem space.
- Gathering training data at scale.
- Exploring model design and architecture.
- Exploring learning objectives and tasks.
- Build Feature Generation Algorithms.
- Build Automated Document Understanding Training Pipelines.
- Guide team members to develop new technologies that lead to solutions that impact real production scenarios
Required Qualifications
- Master’s Degree or Above in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 10+ years related experience (e.g., statistics, predictive analytics, research)
- 8+ years of experience in product development in the areas of Software Engineering and ML (Deep Learning).
- Hands-on experience in developing algorithms and models using deep learning frameworks such as TensorFlow, PyTorch, etc.
- Experience with Search/recommendations.
Qualifications (preferred)
- Potential to think big, while showing progress with real world impact during design and development.
- Actively conducting research in at least one of the following areas: artificial intelligence, data science, information retrieval, machine learning, and natural language processing.
- Understanding and knowledge of web data documents understanding concepts, methods, applications, and challenge
- Experience writing efficient and reusable code and executing complex experiments involving large AI models and high-volume, high-dimensional data from varying sources.
- Strong communication skills for articulating research ideas, results, and the impact of innovations both within the organization and in the broader research community.
The typical base pay range for Applied Sciences across the U.S. is USD $137,600 – $267,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and Seattle Washington, and the base pay range for this role in those locations is USD $180,400 – $294,000 per year.
If you are interested with this position, please send your CV to pocketai@smartpocketai.com
Updated on Oct/01/2024