AI/ML Engineer with Knowledge of Front End

Role Overview

The AI/ML Engineer will be responsible for designing, training, fine-tuning, and optimizing AI/ML models, with a strong focus on Agentic AI systems capable of autonomous reasoning, planning, and action execution. The role involves working closely with product, platform, and engineering teams to deploy scalable, efficient, and secure AI models in production environments.

Key Roles & Responsibilities

01: Agentic AI Model Development

• Design and implement agentic AI architectures (multi-agent systems, tool-using agents and planners)
• Develop autonomous agents capable of decision-making, reasoning, and task execution
• Integrate LLM-based agents with external tools, APIs, workflows, and SDKs

02: Model Training & Fine-Tuning

• Fine-tune LLMs and foundation models using techniques such as:
• Supervised Fine-Tuning (SFT)
• Reinforcement Learning from Human Feedback (RLHF)
• Preference Optimization (DPO, PPO)
• Train domain-specific models using structured and unstructured datasets
• Prepare, clean, label, and validate training datasets

03: Model Optimization

• Optimize models for latency, memory, and cost efficiency
• Apply techniques such as:
• Quantization
• Pruning
• Knowledge distillation
• Low-Rank Adaptation (LoRA / QLoRA)
• Enable efficient inference on cloud, edge, or hybrid environments

04: Evaluation & Validation

• Define evaluation metrics for:
• Accuracy
• Reasoning quality
• Hallucination reduction
• Task success rate
• Perform benchmarking and A/B testing
• Conduct bias, robustness, and adversarial testing