AI/ML IOT engineer - SQA

HTC Global Services; Hyderabad; On-site; INR 2,000,000 - 3,200,000; Full time

Job summary

HTC Global Services is seeking a highly skilled AI/ML IoT engineer - SQA with 5+ years of industry experience to design and execute test strategies for ML/DL models on IoT edge devices, validate accuracy and robustness, and ensure integration across firmware, middleware, connectivity and cloud APIs.

You will build automated testing frameworks for data pipelines, feature extraction, inference performance, and edge/cloud integration, collaborating with ML developers and aligning validation with

Qualifications

• Strong understanding of ML frameworks such as TensorFlow, PyTorch, scikit-learn.
• Experience designing and executing automated test frameworks for ML/DL systems.
• Familiarity with DevOps tools like Docker, Kubernetes, Jenkins, GitLab CI.
• Exposure to ML model optimization for edge devices (e.g., TensorRT, OpenVINO, Edge TPU).
• Knowledge of MLOps practices, including model versioning and deployment workflows.
• Understanding of natural language processing and Tiny LLMs is a plus.

Responsibilities

• Develop and execute test strategies for ML/DL models on IoT edge devices.
• Validate model accuracy, robustness, and scalability under real IoT data conditions.
• Design automated frameworks to test data pipelines, feature extraction, inference performance.
• Ensure seamless integration of ML/DL modules into the IoT platform stack.
• Collaborate with ML developers to ensure models meet production-grade quality standards.
• Work with DevOps engineers to integrate ML model validation into CI/CD workflows.

Skills

TensorFlow

PyTorch

scikit-learn

Automated ML testing

MLOps practices

Tiny LLMs / NLP

Tools

Docker

Kubernetes

Jenkins

GitLab CI

TensorRT

OpenVINO

Job description

About the Role:

We are looking for a highly skilled AI/ML IOT engineer - SQA with

5+ Years of relevant industry experience.

• Develop and execute test strategies for machine learning, deep learning, and Tiny LLM models running on IoT edge devices.
• Validate model accuracy, robustness, and scalability under real-world IoT data conditions.
• Design automated frameworks to test data pipelines, feature extraction, inference performance, and edge/cloud integration.
• Ensure seamless integration of ML/DL modules into the IoT platform software stack (firmware, middleware, connectivity, and cloud APIs).
• Collaborate with ML developers to ensure models meet production-grade quality standards.
• Work with DevOps engineers to integrate ML model validation into CI/CD workflows.

Job Description

About the Role:

We are looking for a highly skilled AI/ML IOT engineer - SQA with

5+ Years of relevant industry experience.

Key Responsibilities

• Develop and execute test strategies for machine learning, deep learning, and Tiny LLM models running on IoT edge devices.
• Validate model accuracy, robustness, and scalability under real-world IoT data conditions.
• Design automated frameworks to test data pipelines, feature extraction, inference performance, and edge/cloud integration.
• Ensure seamless integration of ML/DL modules into the IoT platform software stack (firmware, middleware, connectivity, and cloud APIs).
• Collaborate with ML developers to ensure models meet production-grade quality standards.
• Work with DevOps engineers to integrate ML model validation into CI/CD workflows.

Requirements

• Strong understanding of machine learning frameworks such as TensorFlow, PyTorch, scikit-learn.
• Experience in designing and executing automated test frameworks for ML/DL systems.
• Familiarity with DevOps tools like Docker, Kubernetes, Jenkins, GitLab CI.
• Exposure to ML model optimization for edge devices (e.g., TensorRT, OpenVINO, Edge TPU).
• Knowledge of MLOps practices, including model versioning and deployment workflows.
• Understanding of natural language processing and Tiny LLMs is a plus.