
Applied Scientist II
- Noida, Uttar Pradesh
- Permanent
- Full-time
- You will work on machine learning (ML) projects across various domains like natural language processing (NLP), Vision and harness LLMs, VLMs, and Diffusion models to deliver visual AI solutions for our customers.
- You will get the opportunity of working in a fast-paced environment developing algorithms and techniques leveraging text, and images for analyzing and transforming content to build solutions that have the potential to transform people’s lives.
- You will work with engineering partner teams on the model integration/flight/maintenance.
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research)
- OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
- OR equivalent experience.
- Proficiency in Python and relevant ML libraries (e.g., PyTorch).
- Experience with LLM/VLM/diffusion models (e.g., GPT, Deepseek-R1, Stable diffusion, Phi-V, Qwen).
- Technical background in coding and design, specifically in the development of AI models for scaled production services.
- Demonstrated success in shipping applied research to production, highlighting a track record of combining coding skills with advanced expertise in AI model development.
- Problem solving and data analysis skills, with expertise in developing or applying predictive analytics, statistical modelling, data mining, or machine learning algorithms.
- Leadership skills to influence others, with the ability to understand team dynamics, retain, attract, and develop team members.
- Grounded in growth mindset, and advocate for diversity and inclusion.
- Customer obsessed and passionate about product impact.