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Company Description Polaris Aviation Private Limited is a DPIIT-recognized startup and registered MSME operating at the intersection of aviation and technology. The company combines deep expertise in flight operations and aviation regulation with strong software, cloud, and AI engineering capabilities to build mission-grade systems for regulators, training organizations, and operators. Its work centers on AI-enabled platforms that support real-world aviation use cases such as licensing, assessment, training, and operational oversight. Based in India and aligned with Digital India, Make in India, and Atmanirbhar Bharat, Polaris Aviation develops indigenous aviation technology designed for local operational realities while being scalable to global, non–English-first and emerging markets.
Role Description This is a full-time foundational AI research role in a hybrid setup, with the primary location in New Delhi and some work-from-home flexibility. The role involves designing, prototyping, and evaluating core AI models and algorithms to address complex aviation-specific problems, including licensing, assessment, training, and safety oversight. The person in this position will conduct literature reviews, explore new architectures and learning paradigms, build experimental pipelines, and collaborate with engineering teams to transition research outputs into production-ready systems. Daily tasks include data exploration and curation, defining research hypotheses, running experiments, analyzing results, and documenting findings in clear technical reports. The role also includes close collaboration with domain experts in aviation operations and regulation to ensure that research outcomes are grounded in real operational needs and can be effectively integrated into Polaris Aviation’s AI-enabled platforms.
Qualifications
- Strong foundation in machine learning and deep learning, including experience with model architectures, training paradigms, and evaluation methodologies.
- Hands-on experience with modern AI frameworks and tools (e.g., PyTorch, TensorFlow, JAX, Hugging Face, experiment tracking and MLOps tooling).
- Solid background in mathematics and statistics relevant to AI research (e.g., linear algebra, probability, optimization, information theory).
- Proficiency in programming for research and prototyping (e.g., Python, data processing, reproducible experiments, version control with Git).
- Experience in working with real-world datasets, including data cleaning, preprocessing, feature engineering, and handling imperfect or noisy data.
- Ability to design and run empirical studies, interpret results rigorously, and communicate insights clearly in written and spoken form.
- Graduate or postgraduate degree in computer science, AI, data science, applied mathematics, or a related field, or equivalent practical research experience.
- Interest in aviation, safety-critical systems, or regulated domains; prior exposure to aviation operations or regulatory environments is a plus.
- Comfort working in a startup environment, including collaborating across disciplines
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