Ai Ml Engineer

Tekskills; Karnataka; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Tekskills is seeking a seasoned AI/ML engineer in Karnataka to design and develop cutting-edge models. You will work on CNN/RNN/GNN/Transformers architectures, implement in Python using PyTorch or TensorFlow, and tackle vision, time-series, and multimodal data problems.

The role requires 4+ years total experience with 3+ years in AI/ML, and a strong background in deep learning and related techniques. Collaboration with cross-functional teams on real-world product and research applications is

Qualifications

• M.Tech in AI/ML with EC or CS background as mandatory qualification.
• Total experience 4+ years, with at least 3+ years in AI/ML domain.
• Proficiency in DL architectures (CNN/RNN/GNN/Transformers), Python, and major ML frameworks.

Responsibilities

• Collaborate with cross-functional teams on real-world product and research applications.

Skills

CNN

RNN

GNN

Transformers

Python

PyTorch

TensorFlow

Computer Vision

Time-series analysis

Video analysis

Unsupervised learning

Semi-supervised learning

Education

M.Tech in AI/ML with EC or CS

Job description

Hi we are hiring for

Mandatory:

• M.Tech in AI/ML with background in Electronics & Communication (EC) or Computer Science (CS).
• Experience: 4+ years total, with at least 3+ years relevant in AI/ML domain.

Core Skillset (Must-Have):

• Expertise in Deep Learning architectures: CNN, RNN, GNN, Transformers.
• Strong programming skills in Python.
• Experience with at least one major AI/ML framework (PyTorch / TensorFlow).
• Track record in Computer Vision, Time-Series Analysis, Video Analysis.
• Familiarity with Unsupervised & Semi-supervised learning techniques.

Preferred/Good to Have:

• Image Processing, NLP, Edge/Embedded AI deployment
• Design and develop cutting-edge AI/ML models for vision, time-series, and multimodal data.
• Research and prototype advanced algorithms using state-of-the-art methods in deep learning.
• Optimize models for performance and scalability across platforms.
• Collaborate with cross-functional teams on real-world product and research applications.