Senior AI Engineer

This role is for one of the Weekday's clients

Salary range: Rs 4000000 - Rs 5000000 (ie INR 40-50 LPA)

Min Experience: 5 years

Location: Mumbai, Navi Mumbai, Pune, Nashik

JobType: full-time

Key Responsibilities:

• AI Model Development & Implementation: Design, develop, and implement AI/ML models tailored to business needs.
• Model Deployment: Deploy AI models in production environments using cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
• MLOps & Automation: Build and maintain machine learning pipelines following MLOps best practices to ensure efficient deployment and scaling.
• Performance Optimization: Continuously fine-tune models to improve efficiency, accuracy, and scalability.
• Cross-Functional Collaboration: Work closely with data scientists, software engineers, and domain experts to integrate AI solutions into applications.
• Continuous Learning & Innovation: Stay updated with the latest advancements in AI/ML to drive innovation and improve model performance.

Requirements

Required Skills & Qualifications:

• Experience: 5+ years of hands-on experience in AI/ML development and deployment.
• Programming: Strong proficiency in Python and experience with ML frameworks like TensorFlow, PyTorch, Keras, or Scikit-learn.
• Cloud & AI Services: Experience with cloud-based AI services such as AWS SageMaker, Google Vertex AI, or Azure ML.
• Deep Learning & NLP: Strong understanding of deep learning architectures (CNNs, RNNs, Transformers) and Natural Language Processing (NLP) techniques.
• Data Processing & Storage: Proficiency in SQL, NoSQL, Spark, Hadoop for handling large-scale data.
• MLOps & Model Deployment: Expertise in model versioning, CI/CD pipelines, and automated deployment.
• API Integration: Experience integrating AI models into applications via APIs.

Preferred Qualifications:

• CI/CD & DevOps: Experience with CI/CD pipelines for machine learning workflows.
• Edge AI: Familiarity with deploying AI models on mobile, IoT devices, or edge computing environments.
• Advanced AI Techniques: Experience in Generative AI, Reinforcement Learning, Large Language Models (LLMs), and Federated Learning.