Description

You will develop and validate AI/ML models and implement scalable machine learning pipelines for IT/OT products.

This role is on-site.

Responsibilities

• Build and scale Deep Learning models with optimal parallelism on CPUs and GPUs.
• Research, fine-tune, and serve state-of-the-art LLMs for various business use cases.
• Optimize distributed training execution, including hyperparameter optimization and inference latency.
• Collaborate with Data Science and Data Engineering teams to solve machine learning challenges at scale.
• Maintain model performance, uptime, and scale through rigorous monitoring and high code quality.

Required Skills

• 3+ years of industry experience with Python in a programming intensive role.
• 3+ years of experience with distributed computing frameworks like Spark or the Kubernetes ecosystem.
• 3+ years of experience with ML frameworks including PyTorch, TensorFlow, Keras, or Spark MLlib.
• 3+ years of experience with major cloud computing services and Azure ML.
• 2+ years of experience in machine learning topics such as classification, clustering, optimization, recommendation systems, or deep learning.
• Experience with HuggingFace Transformers and libraries like scikit-learn, spaCy, or gensim.
• Experience building and scaling Generative AI applications using Langchain, PGVector, or Pinecone.
• Proficiency in PySpark, containerization, and CI/CD frameworks.
• MS or Ph.D. in Computer Science, Software Engineering, Electrical Engineering, or a related field.

Preferred Skills

• Experience designing scalable services controller architecture using FastAPI.
• Track record of building and scaling data products.

Key Skills

Education

Any Graduate