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 recent 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