AI Engineer | Remote--100% Placement

Hi Everyone,

Greetings!!

We have an immediate opening for Senior AI Engineer | Remote. Please go through the requirement and reply with your updated profile, contact details, and your availability if you would be interested in it.

Job Title: Senior AI Engineer

Location: Remote

Duration: Long Term

Job Description

A highly skilled Generative AI / Large Language Model Specialist with expertise in domain-specific dataset preparation, advanced fine-tuning, and multi-step agentic system design.

The ideal candidate will have hands-on experience working with medical data, along with a strong background in reinforcement learning, reward modelling, and embedding optimization.

Key Responsibilities:

1. Domain-Specific Dataset Preparation Curate, preprocess, and structure medical chart datasets, including comprehensive patient records (medical history, diagnoses, treatments, test results) while adhering to compliance and privacy requirements.
2. Tokenization for Specialized Data Apply and optimize tokenization strategies tailored to domain-specific language, ensuring high model efficiency and accuracy.
3. Advanced LLM Fine-Tuning Perform parameter-efficient and full fine-tuning of LLMs, incorporating reinforcement learning with human feedback (RLHF) and reward modelling techniques.
4. Model Evaluation & Benchmarking Define and implement fine-tuned evaluation metrics, benchmark models, and analyse system performance to ensure reliability and accuracy.
5. Agentic Architecture Design Architect and implement multi-step, reasoning-capable AI agents, leveraging embedding tuning for optimal task execution.

Qualifications:

• Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or related field
• Proven track record in medical NLP or domain-specific LLM projects.
• Strong understanding of transformer architectures, embedding models, and prompt engineering.
• Proficiency in Python and ML frameworks (e.g., PyTorch, Cuda).
• Familiarity with RLHF, reward modelling, and evaluation frameworks.

Nice to Have:

• Prior work in multi-agent AI systems.
• Experience with embedding Optimization vector databases and knowledge graphs.
• Contributions to open-source LLM projects.

Principal AI Engineer Expectations :

• Should be able to fine-tune models, especially in contexts where the architecture differs from standard setups. 1
• Must guide the team in reinforcement learning and resolve issues during fine-tuning, articulating solutions clearly. 2
• Needs experience in deep learning training; prior LLM fine-tuning is a plus but not mandatory, as deep learning experience is considered sufficient to understand LLM fine-tuning requirements. 3
• Should have expertise in advanced agentic AI, including multi-step RAG (Retrieval-Augmented Generation) solutions, architecting tools, MCP servers, writing advanced RAG code, and benchmarking both fine-tuned and RAG models. 4

Senior AI Engineer Expectations:

• Should consult with the principal engineer to develop advanced RAG models, not just basic or naive RAG implementations. 1
• Expected to build multi-step or advanced RAG systems, including features like self-reflection, grading, and using cross-encoders or bi-encoders. 2
• Some engineers should be skilled in RAG development, while others should focus on fine-tuning models, with a mix of expertise across the team. 3

Thanks & Regards

Ravinder Molugu

Direct:

Desk: Ext: 172

E-mail:

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