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.
