AI Engineer - Larage Language Models (5-8 yrs)

Job Description : AI Engineer

Position Overview

We are seeking a highly skilled and experienced AI Engineer with 5-8 years of expertise to design, develop, and deploy intelligent data-driven solutions. The ideal candidate will have a proven track record in machine learning, natural language processing, large language models (LLMs), and automation, with a focus on delivering scalable and innovative solutions for complex business challenges.

Key Responsibilities :

- Design and implement machine learning models and algorithms for structured and unstructured data.

- Develop and deploy intelligent document processing solutions to extract, validate, and structure data.

- Build and enhance conversational AI frameworks using natural language processing (NLP) techniques and large language models (LLMs) such as ChatGPT, Gemini, and LLaMA.

- Integrate LLMs into applications for contextual understanding, content generation, and decision-making processes.

- Automate end-to-end workflows, including chatbot development, data extraction, and system integration, to improve operational efficiency.

- Collaborate with cross-functional teams to understand business requirements and translate them into LLM-powered solutions.

- Ensure AI/ML and LLM-based solutions are scalable, reliable, and compliant with security and privacy standards.

- Continuously monitor and optimize the performance of deployed LLMs and AI/ML systems, including fine-tuning and retraining as needed.

- Research and integrate state-of-the-art advancements in LLMs and AI/ML into existing and new projects.

- Document workflows, methodologies, and best practices for LLM and AI model usage to promote knowledge sharing and scalability.

Required Technical Expertise

- Proficiency in Python for data analysis, LLM fine-tuning, and automation.

- Hands-on experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).

- Expertise in large language models (LLMs) such as ChatGPT, Gemini, LLaMA, and open-source alternatives.

- Experience in leveraging APIs of LLM platforms like OpenAI, Google Gemini, and Meta AI.

- Familiarity with tools for LLM fine-tuning, reinforcement learning from human feedback (RLHF), and custom deployment.

- Strong knowledge of NLP techniques and frameworks (e.g., Hugging Face Transformers, spaCy, NLTK).

- Experience in OCR tools and libraries (e.g., Tesseract, Google OCR) for intelligent document processing.

- Familiarity with chatbot frameworks (e.g., LangChain, Haystack, Dialogflow) and web scraping tools (e.g., BeautifulSoup, Scrapy, Playwright).

- Knowledge of cloud platforms (e.g., GCP, AWS, Azure) for deploying and managing AI and LLM solutions.

- Strong understanding of MLOps tools (e.g., MLflow, Kubeflow, Vertex AI) for model management and pipeline automation.

Qualifications :

- Bachelor's or Master's degree in Computer Science or related fields.

- 5-8 years of hands-on experience in AI, machine learning, and NLP-focused roles.

- Proven ability to build, fine-tune, and deploy LLM-based solutions in production environments.

- Excellent analytical, problem-solving, and communication skills.

- Strong attention to detail and commitment to delivering high-quality solutions.

Preferred Skills :

- Advanced understanding of LLM deployment strategies, including prompt engineering and fine-tuning.

- Knowledge of AI model monitoring tools for detecting performance drift, bias, and errors in LLM and AI/ML systems.

- Familiarity with data security and regulatory requirements, particularly for sensitive domains like banking.

- Experience in API development and system integration frameworks for LLM-powered applications.

- Research-driven mindset to stay updated on advancements in LLMs, including emerging models and use cases.

- Excellent/Good communication skills

Willing to work in : 1-10 shifts

WFO : BLR Location - 5days a week

Immediate to 15 days joiner

Banking domain Must

Should be willing to travel onsite for short or long term