AI /ML ENGINEER ( 1 - 3 YRS EXP)

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.

Experience: 1 - 3  years of experience
Work From Office
Trivandrum
Salary : 5- 9 LPA

Key Responsibilities

1.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.

2.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.

3.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.

4.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.

5.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.

6.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.)

7. 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.

8.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.