Sr. AI ML Developer

Tata Consultancy Services; Hyderabad; On-site; INR 1,800,000 - 3,600,000; Full time

Job summary

Tata Consultancy Services is seeking an experienced AI/ML engineer to design and deploy models for edge devices. You will work with TensorFlow Lite, PyTorch Mobile, and ONNX, optimizing performance on Raspberry Pi, Jetson Nano, and Coral Dev Board. Proficiency in Python and C/C++, plus Docker/Kubernetes, CI/CD, is essential.

Strong data analysis and many ML domains expected. Join a team focused on edge AI with opportunities to work across CV, NLP, and ML applications, leveraging accelerators and

Qualifications

• 8+ years hands-on development experience in AI/ML.
• Strong knowledge of ML libraries (TensorFlow Lite, PyTorch Mobile, ONNX).
• Experience with edge hardware platforms (e.g., Raspberry Pi, Jetson Nano, Coral Dev Board).
• Proficient in Python and C/C++.
• Familiarity with performance optimization techniques for models on edge.
• Experience with REST APIs, messaging protocols, or low-latency data streaming.
• Ability to perform predictive and statistical analysis from different data sources.
• Experience building and deploying AI models on edge devices.
• Knowledge of embedded systems, microcontrollers, or low-power compute devices.
• Experience with Docker, Kubernetes, and CI/CD pipelines.
• Experience with Image Processing, Computer Vision, NLP, Pattern Recognition, Machine Learning and Linear algebra.
• Exposure to AI accelerator frameworks.

Skills

AI/ML development

ML libraries

Edge computing

Python

C/C++

Performance optimization

REST APIs

Data analysis

Embedded systems

Docker

Kubernetes

CI/CD pipelines

AI accelerator frameworks

Computer Vision

Tools

TensorFlow Lite

PyTorch Mobile

ONNX

Docker

Kubernetes

CI/CD

Job description

• 8+ years of hands-on development experience in AI/ML.
• Strong knowledge of ML libraries (TensorFlow Lite, PyTorch Mobile, ONNX).
• Experience with edge hardware platforms (e.g., Raspberry Pi, Jetson Nano, Coral Dev Board).
• Proficient in Python and C/C++.
• Familiarity with performance optimization techniques for models on edge.
• Experience with REST APIs, messaging protocols, or low-latency data streaming.
• Ability to perform predictive and statistical analysis from different data source
• knowledge and hands-on experience of building and deploying AI models on edge devices.
• knowledge of embedded systems, microcontrollers, or low-power compute devices.
• Experience with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines
• Experience with Image Processing, Computer Vision, NLP, Pattern Recognition, Machine Learning and Linear algebra.
• knowledge and exposure to model optimization techniques.
• Experience with AI accelerator frameworks