Foundation Model Engineer

8 hours ago

Bengaluru, Karnataka, India ZenteiQ Full time ₹ 20,00,000 - ₹ 25,00,000 per year

Company Description

is at the forefront of building India's sovereign scientific AI future, specializing in Scientific Foundation Models (SFM) that merge physics, mathematics, and data. Selected by IndiaAI MeitY, we lead the development of India's Scientific Foundation Model to advance AI capabilities in strategic and engineering domains. Unlike traditional language models that learn from text, SFM focuses on equations, simulations, and fundamental engineering principles to provide reliable and physics-consistent outputs. Our goal is to compress R&D cycles, enabling faster innovation with AI that relies on causality rather than correlation. Founded by Indian Institute of Science (IISc) faculty and based in Bengaluru, leverages cutting-edge research excellence to lead the development of globally competitive, engineering-grade AI.

Role Description

This is an on-site role based in Bengaluru for a Foundation Model Engineer. The Foundation Model Engineer will contribute to building and optimizing scientific foundation models, focusing on designing, implementing, and testing AI solutions that integrate fundamental physics and mathematical principles. Daily tasks include developing algorithms, conducting experiments, optimizing model performance, and collaborating closely with researchers and engineers. The role demands a commitment to advancing the state of engineering-grade AI through innovative approaches and research-driven methodologies.

Qualifications

  • Proficient in Machine Learning, Deep Learning, and AI algorithms.
  • Strong programming skills in Python, TensorFlow, PyTorch, and familiarity with numerical computing libraries.
  • Deep understanding of physics-based modeling, numerical simulations, and mathematical frameworks.
  • Experience with data preprocessing, feature engineering, and datasets creation for scientific models.
  • Excellent problem-solving abilities in applying first principles to build physics-consistent AI solutions.
  • Strong collaboration and communication skills to work in a research-intensive, multidisciplinary team.
  • A Master's or Ph.D. in Computer Science, Mathematics, Engineering, or related fields is preferred.
  • Knowledge of deploying machine learning models at scale and familiarity with cloud AI frameworks is a plus.

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