AI ENGINEER - Experienced

Overview

We are looking for an experienced AI Engineer to join our team. The ideal candidate will have a strong background in designing, deploying, and maintaining advanced AI/ML models with expertise in Natural Language Processing (NLP), Computer Vision, and architectures like Transformers and Diffusion Models. You will play a key role in developing AI-powered solutions, optimizing performance, and deploying and managing models in production environments.

Key Responsibilities

• AI Model Development and Optimization:
• Design, train, and fine-tune AI models for NLP, Computer Vision, and other domains using frameworks like TensorFlow and PyTorch.
• Work on advanced architectures, including Transformer-based models (e.g., BERT, GPT, T5) for NLP tasks and CNN-based models (e.g., YOLO, VGG, ResNet) for Computer Vision applications.
• Utilize techniques like PEFT (Parameter-Efficient Fine-Tuning) and SFT (Supervised Fine-Tuning) to optimize models for specific tasks.
• Build and train RLHF (Reinforcement Learning with Human Feedback) and RL-based models to align AI behavior with real-world objectives.,
• Explore multimodal AI solutions combining text, vision, and audio using generative deep learning architectures.
• Natural Language Processing (NLP):
• Develop and deploy NLP solutions, including language models, text generation, sentiment analysis, and text-to-speech systems.
• Leverage advanced Transformer architectures (e.g., BERT, GPT, T5) for NLP tasks.
• AI Model Deployment and Frameworks:
• Deploy AI models using frameworks like VLLM, Docker, and MLFlow in production-grade environments.
• Create robust data pipelines for training, testing, and inference workflows.
• Implement CI/CD pipelines for seamless integration and deployment of AI solutions.
• Production Environment Management:
• Deploy, monitor, and manage AI models in production, ensuring performance, reliability, and scalability.
• Set up monitoring systems using Prometheus to track metrics like latency, throughput, and model drift.
• Data Engineering and Pipelines:
• Design and implement efficient data pipelines for preprocessing, cleaning, and transformation of large datasets.
• Integrate with cloud-based data storage and retrieval systems for seamless AI workflows.
• Performance Monitoring and Optimization:
• Optimize AI model performance through hyperparameter tuning and algorithmic improvements.
• Monitor performance using tools like Prometheus, tracking key metrics (e.g., latency, accuracy, model drift, error rates etc.)
• Solution Design and Architecture:
• Collaborate with cross-functional teams to understand business requirements and translate them into scalable, efficient AI/ML solutions.
• Design end-to-end AI systems, including data pipelines, model training workflows, and deployment architectures, ensuring alignment with business objectives and technical constraints.
• Conduct feasibility studies and proof-of-concepts (PoCs) for emerging technologies to evaluate their applicability to specific use cases.
• Stakeholder Engagement:
• Act as the technical point of contact for AI/ML projects, managing expectations and aligning deliverables with timelines.

Participate in workshops, demos, and client discussions to showcase AI capabilities and align solutions with client needs.

Experience: 2.5 - 5 years of experience
Salary : 5-11 LPA

Job Types: Full-time, Permanent

Pay: ₹500,000.00 - ₹1,100,000.00 per year

Schedule:

• Day shift

Work Location: In person