You will be joining Near, one of the fastest-growing Enterprise SaaS companies (NASDAQ: NIR). You will experience a truly agile culture with the freedom to experiment and innovate. At Near, we believe great culture is not just about work; it’s work + life. We not only encourage our employees to dream big and innovate but also give them the freedom and the tools to do so.
Near is the world’s largest data intelligence company sourcing varied data about people, places, and products. Near builds a wide variety of decision-support tools based on this data to enable everyday decision-making in enterprises across various functional areas including marketing and operational aspects. Research at Near focuses on developing fundamental first-principles-based technologies on a variety of data, modeling, and compute-related problems from multiple aspects such as the following:
This will be a work-from-office role, based in our state-of-the-art office in Koramangala, Bangalore.
A Day in the Life
- Modeling a domain to account for incomplete or noisy data and enable the imputation of data.
- Techniques to characterize and estimate steady-state and dynamic properties of large-scale aggregate human behavior, geospatial data, and other types of data exhaust – real-time and historical.
- Building predictive models to estimate various properties of different systems – given small/large data samples.
- Adapt existing signal processing and estimation techniques to improve decision support at different time scales.
- Build models of various types/modes at different levels of granularity and confidence that integrate disparate data.
- Build models of various types/modes at different levels of granularity and confidence that integrates disparate data.
- Develop new algorithmic techniques that analyze data with a wide variety of constraints including privacy constraints, access constraints, embedded errors and noise, and more including video/image/text/speech/unstructured data processing technologies.
What You Bring to the Role
- Graduate work in Generative AI technologies and familiarity with state-of-the-art technologies to drive our R&D program.
- Ph.D. in Applied Math, Probability & Statistics, Computer Science, Operations Research, Engineering, or any compute-related field with thesis work related to generative AI technologies.
- The ideal candidate should have hands-on experience in Deep Learning, Generative AI, Transformer tech, and large-scale big-data/computing.
- The ideal candidate should have academic or applied industrial R&D experience.
- Familiarity with programming, and data analysis – the ability to think critically.
- Industry experience of 3-5 years is a plus.
- To demonstrate the capability to formulate and work on problems independently, the candidate must have published 1- 3 research papers in peer-reviewed conferences and/or journals.
- The candidate is expected to have exceptional problem-solving, analytical, and organizational skills with a detail-oriented attitude.
- Word experience in the Enterprise SaaS/Data Intelligence/Operational Intelligence industry is a plus.
- Passion for learning new technologies and solving real-world problems for global impact.
- Be up-to-date with the scientific research community and developments.
- Good communication skills – presentations, written technical reports.