Machine Learning Engineer

Job Description We are seeking a skilled

Ai Ml Engineer | Delhi having 4+ yrs with strong experience in designing and developing scalable enterprise applications.

About Us CodeVyasa is a mid-sized product engineering company that works with top-tier product and solutions organizations such as McKinsey, Walmart, RazorPay, Swiggy, and others. We are a team of 550+ engineers, driving innovation across Product & Data Engineering, focusing on Agentic AI, RPA, Full Stack, and GenAI-based solutions.

Key Responsibilities

• Design, develop, train, fine-tune, and deploy AI/ML models for business applications.
• Build end-to-end machine learning pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment.
• Develop AI solutions in domains such as

Natural Language Processing (NLP) ,

Computer Vision , or

Predictive Analytics .

• Implement and optimize deep learning models using

PyTorch ,

TensorFlow , and

Keras .

• Utilize

Hugging Face libraries and pretrained models for NLP and transformer-based AI applications.

• Process and analyze structured and unstructured data using Python data science libraries.
• Build scalable inference services and integrate AI models into enterprise applications.
• Deploy, monitor, and maintain machine learning models in production environments.
• Collaborate with Data Engineers and DevOps teams to build reliable ML pipelines and MLOps workflows.

Required Skills AI/ML Model Development

• 4-7 years of hands-on experience developing, training, fine-tuning, and deploying AI/ML models.
• Strong understanding of supervised, unsupervised, and deep learning techniques.
• Experience delivering production-ready AI solutions. Python & AI Frameworks
• Strong proficiency in

Python .

• Hands-on experience with:
• PyTorch
• TensorFlow
• Keras
• Hugging Face
• Experience implementing transformer-based models and deep learning architectures.

Why Join CodeVyasa?

• Work on innovative, high-impact projects with leading global clients.
• Exposure to modern technologies, scalable systems, and cloud-native architectures.
• Continuous learning and upskilling opportunities through internal and external programs.
• Supportive and collaborative work culture with flexible policies.
• Competitive salary and comprehensive benefits package.
• Free healthcare coverage for employees and dependents.