Generative AI Engineer /Lead /Architect

Role: Generative AI Engineer /Lead /Architect
Location: Remote
Mandatory Skills : AWS Sagemaker , AWS BedRock , Generative AI

Job Overview:
AWS Experience - AWS Sagemaker is required, AWS BedRock would be a nice to have.
Model Building, Accuracy Metrics, Finetuning - standard Data Science skillset.
Proven expertise in model finetuning for LLMs - PEFT, LORA techniques would be a big plus.
Able to understand what technique to use for data type.
RAG Experience would be great to have - similar to AI Engineer.

Machine Learning Engineering:

• Develop, train, and deploy ML models, ensuring they are optimized for production environments.
• Create and maintain automated feedback loops to enhance model accuracy and performance.
• Implement ML pipelines for continuous evaluation and refinement of models in production.

AI Orchestration & Integration:

• Integrate Large Language Models (LLMs) into business applications.
• Build AI orchestration systems to manage the end-to-end lifecycle of AI models, including deployment and scaling.
• Work with Vector Databases (VectorDB) to store and query high-dimensional data for AI applications.

Model Evaluation & Feedback Loops:

• Set up evaluation metrics and processes to assess model performance over time.
• Create feedback loops using real-world data to improve model reliability and accuracy.

Text-to-SQL & Generative AI-driven Solutions:

• Develop GenAI-driven Text-to-SQL solutions to automate database queries based on natural language input.
• Optimize GenAI workflows for database interactions and information retrieval.

Embedding/Chunking & Prompt Engineering:

• Design and implement embedding and chunking strategies for scalable data processing.
• Utilize prompt engineering techniques to fine-tune the performance of AI models in production environments.

Required Qualifications:

• Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related field.
• Proven experience in building, deploying, and maintaining ML models in production environments.
• Proficiency in programming languages like Python, and frameworks such as TensorFlow, PyTorch, or similar.
• Familiarity with LLMs, VectorDB, embedding/chunking strategies, and AI orchestration tools.
• Strong understanding of model evaluation techniques and feedback loop systems.
• Hands-on experience with Text-to-SQL and prompt engineering methodologies.
• Knowledge of cloud platforms (AWS) and containerization tools (Docker, Kubernetes).
  
  "Disclaimer: E-Solutions Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state and local laws. We especially invite women, minorities, veterans, and individuals with disabilities to apply. EEO/AA/M/F/Vet/Disability

Generative AI Engineer /Lead /Architect1Generative AI,AWS SageMaker,AWS BedrockN/AC2CUnited States

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