Description :

Job Title : Principal Machine Learning Engineer

Experience : Minimum 5 years

Employment Type : Full-time

About the Role :

We are looking for an experienced Principal Machine Learning Engineer to architect and implement advanced multimodal RAG (Retrieval-Augmented Generation) pipelines that integrate vision and language understanding.

The ideal candidate will bring deep expertise in Machine Learning, Computer Vision, and Natural Language Processing (NLP), with hands-on experience in building scalable AI systems and deploying them using AWS AI services.

Key Responsibilities :

- Architect and implement end-to-end multimodal RAG pipelines, integrating text, image, and other data modalities.

- Apply MLOps best practices for model deployment, monitoring, and continuous improvement using AWS AI services.

- Design and optimize vector databases and embedding retrieval mechanisms for large-scale systems.

- Lead fine-tuning and optimization of Large Language Models (LLMs) using advanced techniques like LoRA, QLoRA, and RLHF.

- Collaborate with cross-functional teams to integrate ML systems into production environments.

- Research and prototype new vision-language models and multimodal architectures.

- Drive scalable deployment strategies for open-source LLMs and manage continuous performance optimization.

- Mentor junior engineers and contribute to the teams overall technical direction.

Required Skills & Qualifications :

- 5+ years of experience in Machine Learning, Computer Vision, NLP, or related fields.

- Strong understanding of multimodal learning and vision-language models.

- Proven experience building and deploying RAG systems and managing vector databases.

- In-depth knowledge of PyTorch, Transformers, and modern ML frameworks.

- Proficiency in NLP, LLM fine-tuning, and model optimization.

- Hands-on experience with AWS AI/ML services, including model deployment and lifecycle management.

- Familiarity with open-source LLM architectures (e.g., LLaMA, Falcon, Mistral, etc.)

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

Preferred Qualifications :

- Experience with multi-cloud or hybrid AI infrastructure.

- Contributions to open-source ML or LLM frameworks.

- Advanced degree (Masters or Ph.D.) in Computer Science, Machine Learning, or related disciplines