Job Summary

Chart the Course for the Future of Flight. This role builds Machine Learning tools to enable reduction of the engineering workforce burden by developing internal ML-based tools across the organisation. This person will develop, research, and deploy ML algorithms across different engineering disciplines.
Roles and Responsibilities
- Research, Develop, and implement machine learning based tools across LLMs, Multimodal systems, Generative AI systems
- Develop training pipelines, architecture, and prototyping for ML algorithms
- Work on productising research prototypes
- Conduct experiments to benchmark current techniques and evaluate model behavior
- Develop systematic evaluation methodology: test sets, accuracy metrics, citation quality scoring, false positive/negative analysis
- Deploy AI tools to engineering teams with structured pilots, baseline measurement, and documented adoption outcomes
Required Qualifications
- 2+ years in developing ML systems with focus on LLM-based products




- Proven understanding of fundamental data structures and the ability to apply them to solve complex problems
- Experience with PyTorch, TensorFlow
- GenAI engineering including concepts relating to scaffolding, harnessing, and RAG pipelines
- Development experience with retrieval pipeline skills (vector databases, chunking strategies, re-ranking, citation grounding)
- Experience with Containerization (Docker/Kubernetes)
Preferred Qualifications
- Understanding and deployment of Reinforcement Learning based tools
- Understanding of mathematics, particularly linear algebra and probability theory
- Experience with distributed processing frameworks and ElasticSearch
- Prior knowledge of multimodal systems and VLM systems
- Experimentation and deployment of Local GenAI model deployment using tools like Olama
- Experience building multi-step agentic workflows

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📌 Machine Learning Engineer (Chennai)
🏢 The ePlane
📍 Chennai