Note: Azure ML / AWS Sage Maker / Google Vertex Certification is required. Won't consider resume without certification.

Location - Bangalore, Chennai, Pune

Exp - 3-5.5 years

Please note - Certification is mandatory.

An AI Engineer is responsible for designing, developing, and deploying autonomous AI that can perform complex tasks with minimal human intervention.

These engineers work with machine learning (ML), reinforcement learning (RL), natural language processing (NLP), and multi-agent systems to create intelligent, adaptable, and scalable AI-driven solutions.

They collaborate with AI researchers, software engineers, and business teams to integrate AI into various applications, including automation, virtual assistants, gaming, finance, and robotics.

Key Responsibilities :

• AI Agent Development & Optimization :

- Design and build autonomous AI capable of decision-making and task execution.

- Implement reinforcement learning algorithms to improve agent performance over time.

- Develop and fine-tune large language models (LLMs) and generative AI for automation and conversational AI.

- Use multi-agent systems (MAS) to coordinate interactions between multiple AI entities.

• Data Processing & Model Training :

- Gather, preprocess, and analyze data to train AI effectively.

- Optimize agents using supervised learning, reinforcement learning (RL), and imitation learning.

- Develop reward functions and environment simulations for RL-based AI.

• AI Deployment & System Integration :

- Deploy AI into real-world applications using cloud platforms (AWS, GCP, Azure).

- Integrate AI with APIs, databases, and third-party software systems.

- Utilize MLOps frameworks to monitor, maintain, and retrain AI.

• Algorithm Research & Experimentation :

- Research and implement cutting-edge AI techniques in agent-based learning and decision-making.

- Experiment with graph neural networks (GNNs), transformers, and neurosymbolic AI for improving agent intelligence.

- Stay updated with advancements in autonomous AI, self-learning models, and cognitive architectures.

• Collaboration & Documentation :

- Work with AI researchers, software developers, and business teams to align AI solutions with real-world needs.

- Write well-documented code and contribute to research papers or AI patents.

- Present findings and technical solutions to non-technical stakeholders.

Required Skills & Qualifications :

• Technical Skills :

- Strong programming skills in Python, C++, or Java.

- Experience with AI/ML frameworks (TensorFlow, PyTorch, Ray RLlib, OpenAI Gym).

- Knowledge of reinforcement learning, deep learning, and multi-agent systems.

- Proficiency in NLP, computer vision, and generative AI techniques.

- Experience with cloud computing, API integration, and real-time AI deployment.

• Mathematical & Analytical Skills :

- Strong understanding of probability, linear algebra, optimization, and game theory.

- Knowledge of decision-making algorithms, planning, and behavioral modeling.

- Ability to build reward functions and environment simulations for AI training.

• Soft Skills :

- Strong problem-solving and analytical thinking.

- Ability to collaborate with cross-functional teams and explain AI concepts clearly.

- Adaptability and willingness to explore emerging AI methodologies.