Job Summary

We are looking for a person with a deep understanding of Machine Learning and Reinforcement learning to develop tools that help us an organisation engineer better systems and also build the platform software that will allow the next generation of mobility to thrive. This person will develop, research, and deploy ML algorithms across different engineering disciplines and build tools for routing, scheduling future mobility transportation networks involving hundreds of aircraft in shared regions.

Roles and Responsibilities
Build and maintain data pipelines for model training, validation, and continuous retraining
Develop training pipelines, architecture, and prototyping for ML/RL 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
Build and operate multi-step agentic workflows connecting engineering data sources for reasoning

Requirements
3+ years ML engineering with a focus on deep learning/reinforcement learning
Solid ML stack:



PyTorch or TensorFlow, Pandas, NumPy, SciPy
Robust programming skills in Python/C++
Hands on experience implementing Neural network architectures like CNNs, Transformers, RNNs, VAEs, Optimization of DL models(Memory, execution time, size) for inference
Working knowledge of full life cycle and various SDLC methodologies to meet project goals
Ability to design production ML systems that fail gracefully and whose failure modes are understood and documented
Reinforcement learning experience: policy training, reward engineering, simulation environment construction

Preferred Qualifications
Gradient-based optimization
Automatic differentiation tools and development
Experience developing ML systems in Safety-critical or regulated domain background where AI output quality must be explainable
Experience building multi-step agentic workflows
Familiarity with aerospace change management processes

Disclaimer: This job posting & Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Machine Learning Engineer Dl/rl Chengalpattu (India)
🏢 The ePlane
📍 India