Senior Machine Learning Engineer (Generative AI)

 Senior Machine Learning Engineer (Generative AI)   About The Role : 

We are looking for an experienced Senior Machine Learning Engineer to collaborate with data scientists and cross-functional teams to develop and deploy cutting-edge AI solutions. This role will focus on engineering robust, scalable systems for Retrieval-Augmented Generation (RAG), large language models (LLMs), advanced recommendation engines, and next-best-action frameworks. The ideal candidate combines deep technical expertise with practical experience in machine learning pipelines, AWS infrastructure, and AI/ML frameworks.

 Roles and Responsibilities 

 AI System Development 

Collaborate with data scientists to build and deploy RAG pipelines, fine-tuned LLMs, and personalized recommender systems.

Design and optimize machine learning pipelines for scalability and performance.

Develop and maintain robust data processing and embedding pipelines for conversational AI and recommendation systems.

 Model Deployment and Optimization 

Deploy machine learning models into production using AWS tools such as SageMaker, Lambda, and DynamoDB.

Optimize models for performance, scalability, and real-time use cases.

Implement monitoring and retraining workflows to maintain model accuracy and relevance.

 Infrastructure and Automation 

Build scalable, secure infrastructure for model deployment and inference using AWS cloud services.

Implement MLOps pipelines for continuous integration, deployment, and model lifecycle management.

Work on vector search implementations and embedding-based retrieval techniques.

 Collaboration and Innovation 

Partner with data scientists to integrate insights and models into production systems.

Collaborate with product teams to design AI-driven features aligned with business goals.

Research and apply emerging technologies to enhance existing systems and workflows.

 Technical Leadership 

Mentor junior team members and provide technical guidance on machine learning best practices.

Conduct code reviews and ensure adherence to software development standards.

Document processes and share knowledge across the team.

 Essential Requirements 

Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field

5+ years of experience in machine learning and software engineering, with expertise in RAG, LLMs, and recommendation systems.

Proficiency in Python and machine learning libraries like TensorFlow, PyTorch, and Scikit-learn.

Strong knowledge of AWS services, including SageMaker, DynamoDB, Lambda, and Aurora.

Familiarity with frameworks like LangGraph.

Experience with embedding-based search and vector databases.

Expertise in building and optimizing machine learning pipelines for production use.

 Plus to Have 

Experience with MLOps practices, CI/CD pipelines, and containerization technologies (e.g., Docker, Kubernetes).

Domain Knowledge of natural language processing (NLP) and conversational AI.