Job Description

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 - 6 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