Senior Software Engineer ML

Overview

Job Responsibilities

• Design and develop machine learning and deep learning systems based on project requirements.
• Fine-tune large language models (LLMs) for specific applications.
• Develop and deploy MLOps pipelines and machine learning models.
• Research and implement appropriate ML algorithms and tools.
• Analyze and improve model performance through rigorous testing and optimization.
• Develop an efficient Retrieval-Augmented Generation (RAG) system, including data indexing,
• chunking, retrieval and response generation.
• Ensure data quality through verification and preprocessing techniques such as data cleaning.
• Write robust backend code using Python.
• Manage available resources, including hardware, data, and personnel, to meet project deadlines. Mandatory Skills
• Minimum 5 years of proven experience as a Machine Learning Engineer, with at least 2 years of
• hands-on experience in Generative AI (Gen-AI) projects.
• Strong understanding of data structures, data modeling and software architecture.
• Proficiency in writing clean and efficient code in Python.
• Experience with machine learning frameworks such as Keras, TensorFlow and PyTorch and libraries like NumPy, Pandas, Matplotlib, Seaborn, OpenCV, and Scikit-Learn.generation.
• Hands-on experience in training deep learning models and hyperparameter tuning.
• Expertise in fine-tuning LLMs for domain adaptation and instruction tuning.
• Experience in RAG system development, including data indexing, chunking, retrieval, and response
• Proficiency in working with LangChain and LlamaIndex frameworks.
• Experience handling JSON/XML data.
• Excellent communication and problem-solving skills.
• Strong analytical and critical-thinking abilities. Good to have skills
• 1. Experience with Django or Flask frameworks.

2. Familiarity with AWS SageMaker and model deployment.
3. Familiarity with Legal and tax domains.

Job Types: Full-time, Permanent

Pay: ₹1,500,000.00 - ₹2,000,000.00 per year

Schedule:

• Day shift

Work Location: In person