Description :

We're looking for an experienced AI Engineer with a passion for Generative AI to join our pioneering team. You'll be instrumental in developing next-generation AI solutions, from fine-tuning Large Language Models (LLMs) to building autonomous AI agents.

If you're excited by the prospect of applying cutting-edge AI to solve complex challenges in industrial and engineering domains, this role is for you.

Key Responsibilities :

- Generative AI Development : Design, develop, and fine-tune Large Language Models (LLMs) and other generative models for specific business applications.

- Agentic AI Systems : Design and build autonomous AI agents capable of reasoning, planning, and using tools to execute complex tasks.

- End-to-End Model Deployment : Manage the entire lifecycle of ML models, including deployment into production and building robust MLOps pipelines.

- System Architecture : Collaborate with cross-functional teams to architect scalable, production-ready systems for generative AI on cloud platforms.

- Research & Prototyping : Stay at the forefront of AI research, rapidly prototyping new models, agents, and algorithms to drive innovation.

- Mentorship : Guide junior engineers and promote best practices in building reliable and efficient AI systems.

Required Skills & Qualifications :

- Experience : 2-4 years of hands-on experience in a machine learning role, with a proven track record of deploying models into production.

- Programming Proficiency : Expert-level skills in Python and its core data science libraries (e.g., NumPy, Pandas, Scikit-learn).

- GenAI & LLM Experience : Demonstrable experience with Generative AI, including LLMs (e.g., GPT series, Llama) and proficiency with frameworks like LangChain, LlamaIndex, or Hugging

Face Transformers.

- ML Frameworks : Deep experience with TensorFlow or PyTorch.

- Cloud Platforms : Strong proficiency in a major cloud provider (AWS, GCP, or Azure) and their ML services (e.g., SageMaker, Vertex AI, Azure ML).

- MLOps Tools : Hands-on experience with MLOps tools and concepts, including Docker,

Kubernetes, and CI/CD pipelines.

Preferred Qualifications :

- An educational or professional background in Civil or Mechanical Engineering is a strong plus.

- Experience building agentic AI systems with capabilities for planning and multi-step reasoning.

- Contributions to open-source AI/ML projects.

- Experience with large-scale data processing frameworks like Spark or Dask.