Senior Machine Learning Engineer
1 week ago
Experience Level: 6-8 Years
Location: Bengaluru
Department: AI & Data Science
About Us:
We are a forward-thinking technology company, committed to delivering innovative and cutting-edge AI-powered solutions to our clients. As part of our ongoing growth, we are looking for a skilled Machine Learning Engineer to join our dynamic team and help build, deploy, and maintain advanced machine learning models for our next-generation products.
Role Overview:
The Machine Learning Engineer will be responsible for implementing and overseeing machine learning algorithms, specifically in the context of Retrieval-Augmented Generation (RAG) systems and the integration of AI agents into Large Language Models (LLMs). The ideal candidate will have a solid background in Python programming, SQL-based databases (MySQL, MS SQL), containerization technologies (Openshift, Kubernetes), as well as expertise in AI supervision and prompt engineering using modern frameworks such as Langchain.
Key Responsibilities:
Develop, deploy, and optimize machine learning models within the RAG (Retrieval-Augmented Generation) backend solution for large-scale applications.
Integrate and supervise AI agents in a Large Language Model (LLM) context, ensuring effective handling of complex data pipelines and operational tasks.
Design, implement, and tune robust machine learning pipelines using Python and related frameworks.
Collaborate with cross-functional teams to understand product requirements and provide innovative AI solutions that meet business needs.
Develop and maintain backend solutions, including the use of MySQL or MS SQL for data management.
Implement and manage AI-driven workflows in a Kubernetes and OpenShift environment to ensure seamless model deployment and scaling.
Perform Prompt Engineering to ensure optimized interaction with large language models, enhancing the quality and accuracy of responses in a RAG context.
Work with the Langchain framework to create and fine-tune prompt engineering strategies and AI agent interactions.
Participate in the evaluation and enhancement of AI models, continually improving their performance and scalability.
Assist in the design and implementation of monitoring tools to track model performance and health in production environments.
Document all stages of development, deployment, and monitoring to ensure smooth collaboration with other engineering teams.
Required Skills & Experience:
6-8 years of experience in machine learning engineering, with a strong focus on AI-driven solutions.
Expert proficiency in Python for developing, optimizing, and deploying machine learning models.
Hands-on experience with MySQL or MS SQL for data manipulation and management in machine learning applications.
Proficiency in Kubernetes and Openshift for deploying, scaling, and managing containerized applications.
Solid understanding and experience in RAG (Retrieval-Augmented Generation) backend solution architectures.
Expertise in integrating AI agents into large language model workflows and understanding the complexities of LLM supervision .
Strong background in prompt engineering , with the ability to create and optimize prompts for LLMs.
Experience working with the Langchain framework for LLM-based applications.
Familiarity with cloud-based architectures and DevOps practices (CI/CD) for deployment automation.
Experience with machine learning libraries such as TensorFlow , PyTorch , scikit-learn , or similar.
Strong problem-solving skills, with a passion for AI and innovative technologies.
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