Responsibilities

• Collaborate with product and software teams to integrate AI solutions and forward-deploy production-grade systems into enterprise applications

• Drive proof-of-concept initiatives and publish insights on emerging techniques

• Orchestrate LLM-based agentic systems

• Contribute in full-cycle AI development, from data pipelines and model training to deployment and monitoring

• Design, build, and optimize production-grade machine learning models

• Implement robust MLOps practices using Kubernetes, MLflow, and cloud services (AWS, Azure, GCP)

• Advocate for ethical AI principles, ensuring fairness, transparency, and security

Qualifications

• BSc/MSc/PhD in Computer Science or related field

• Proficiency in Python, ML frameworks (PyTorch, TensorFlow), and transformer-based architectures

• Proven experience in fine-tuning generative models (e.g. open-source LLMs, diffusion models)

• Experience deploying AI solutions using containerization (Docker, Kubernetes) and CI/CD pipelines.

• Proficiency in at least one agentic orchestration framework for building LLM-based systems

• Comfortable working in AI-first development environments, leveraging agentic tools (e.g., Claude Code, Codex) to plan, build, and iterate faster.

Nice to Have

• Contributions to open-source AI projects

• Expertise in LLM evaluation, and performance-cost optimization

• Experience with advanced AI domains (graph neural networks, reinforcement learning)

• Active engagement in AI communities (Kaggle, Huggingface).

• Experience with agentic orchestration frameworks such as LangGraph, Google ADK, or similar tools