Machine Learning Engineer - DL/RL

Posted One Month Ago
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Chennai, Tamil Nadu, IND
In-Office
Mid level
Aerospace • Hardware • Transportation
The Role
Develop and deploy deep learning and reinforcement learning systems for urban air mobility, including routing and scheduling tools for aircraft networks. Build data and training pipelines, productize research prototypes, optimize inference performance, evaluate model behavior, and deploy AI tools to engineering teams. Responsibilities also include designing reliable production ML systems, constructing simulation environments, engineering rewards, and operating multi-step agentic workflows.
Summary Generated by Built In
About The ePlane Company

The ePlane Company is at the forefront of India's urban air mobility revolution. Incubated at IIT Madras, we are a deep-tech startup dedicated to designing and building the world's most compact electric flying taxi. Our mission is to make door-to-door flying a reality, drastically reducing commute times and decongesting our cities for a cleaner, greener future. We're a passionate team of engineers, designers, and visionaries working on cutting-edge technology, and we're looking for brilliant minds to help us take flight.


Chart the Course for the Future of Flight

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 new 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



RequirementsRequired Qualifications 
  • 3+ years ML engineering with a focus on deep learning/reinforcement learning

  • Strong ML stack: PyTorch or TensorFlow, Pandas, NumPy, SciPy

  • Strong 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


Skills Required

  • 3+ years of machine learning engineering experience focused on deep learning or reinforcement learning
  • Experience with PyTorch or TensorFlow, Pandas, NumPy, and SciPy
  • Strong programming skills in Python or C++
  • Hands-on experience implementing CNN, Transformer, RNN, and VAE neural network architectures
  • Experience optimizing deep learning models for memory, execution time, and size during inference
  • Working knowledge of the full software development life cycle and SDLC methodologies
  • Ability to design production ML systems with understood, documented, and graceful failure modes
  • Experience with reinforcement learning policy training, reward engineering, and simulation environment construction
  • Knowledge of gradient-based optimization
  • Experience with automatic differentiation tools and development
  • Experience developing ML systems in safety-critical or regulated domains where AI output quality must be explainable
  • Experience building multi-step agentic workflows
  • Familiarity with aerospace change management processes
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The Company
Chennai, Tamil Nadu
70 Employees
Year Founded: 2019

What We Do

We're developing India’s 1st flying electric taxi for up to 10x faster intra-city commute and cargo transport. Incubated at IIT Madras, Chennai since 2019, The ePlane Company was founded by Professor Satya Chakravarthy with a vision to make flying ubiquitous. As an Urban Air Mobility (UAM) startup, we aim to alleviate on-road traffic congestion in cities worldwide by offering safe, sustainable and affordable flying experiences through our flagship product, The ePlane e200.

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