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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.
Job Responsibility:
Design, develop, and fine-tune Large Language Models (LLMs) and other generative models for specific business applications
Design and build autonomous AI agents capable of reasoning, planning, and using tools to execute complex tasks
Manage the entire lifecycle of ML models, including deployment into production and building robust MLOps pipelines
Collaborate with cross-functional teams to architect scalable, production-ready systems for generative AI on cloud platforms
Stay at the forefront of AI research, rapidly prototyping new models, agents, and algorithms to drive innovation
Guide junior engineers and promote best practices in building reliable and efficient AI systems
Requirements:
2-4 years of hands-on experience in a machine learning role, with a proven track record of deploying models into production
Expert-level skills in Python and its core data science libraries (e.g., NumPy, Pandas, Scikit-learn)
Demonstrable experience with Generative AI, including LLMs (e.g., GPT series, Llama) and proficiency with frameworks like LangChain, LlamaIndex, or Hugging Face Transformers
Deep experience with TensorFlow or PyTorch
Strong proficiency in a major cloud provider (AWS, GCP, or Azure) and their ML services (e.g., SageMaker, Vertex AI, Azure ML)
Hands-on experience with MLOps tools and concepts, including Docker, Kubernetes, and CI/CD pipelines
Nice to have:
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