AI/ML Engineer

Voxelgrids Innovations Private Limited; India; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Voxelgrids Innovations Private Limited in India seeks a talented AI/ML engineer to develop and evaluate algorithms for MRI image analysis, combining research with practical deployment.

You will build segmentation and classification pipelines, train deep learning models on medical imaging datasets, and collaborate with engineers to translate research into scalable solutions.

Qualifications

• Strong ML/DL fundamentals and Python experience.
• Familiarity with medical imaging or computer vision workflows is a plus.
• Prior AI/ML projects, internships, or research experience preferred.

Responsibilities

• Develop and evaluate AI/ML algorithms for MRI image analysis and automation.
• Build pipelines for image segmentation, classification, detection, quantification, and workflow optimization.
• Train, validate, and optimize deep learning models using medical imaging datasets.
• Develop scalable data processing and model inference pipelines.
• Collaborate with domain experts and engineering teams to translate algorithms into deployable solutions.

Skills

ML fundamentals

Deep learning

Python

PyTorch

Medical imaging

Image analysis workflows

Problem-solving

AI/ML research

Education

Bachelor’s / Master’s in CS/EE/BME/AI/ML

Job description

Qualifications:

• Bachelor’s / Master’s in Computer Science, Electrical Engineering, Biomedical Engineering, AI/ML, Signal Processing, Applied Mathematics, or related fields

Skills:

1. Strong fundamentals in machine learning, deep learning, computer vision, and image processing
2. Hands‑on experience with Python and frameworks such as PyTorch
3. Familiarity with medical imaging, image analysis, or computer vision workflows is a plus
4. Strong analytical and problem‑solving skills
5. Prior AI/ML projects, internships, or research experience preferred

Main Responsibilities:

1. Develop and evaluate AI/ML algorithms for MRI image analysis and automation
2. Build pipelines for image segmentation, classification, detection, quantification, and workflow optimization
3. Train, validate, and optimize deep learning models using medical imaging datasets
4. Develop scalable data processing and model inference pipelines
5. Collaborate with domain experts and engineering teams to translate algorithms into deployable solutions