AWS AI/ML Engineer

AWS AI/ML Engineer

Cincinnati, OH 45202 (100% On-Site)

Responsibilities:

Optimize models for running on embedded hardware or scaling model parallelization on the servers.

Utilize AWS AI services, such as Bedrock, and LLMs like Claude 3 Sonnet, LLaMa, etc. to build intelligent, scalable applications.

Develop and maintain NLP pipelines for risk assessment, threat classification, named entity recognition, information retrieval, summarization etc.

Collaborate closely with Data Science, Cloud Engineering, and Applications Development teams to align on project goals and technical requirements.

Comprehensive knowledge and hands-on experience with fine-tuning approaches and training models.

Lead and contribute to the design and implementation of NLP models and algorithms that can scale across diverse languages and dialects, taking into consideration the linguistic variations and complexities present in different language communities

Perform data preprocessing of structured and unstructured data sources for model serving.

Outstanding communication skills, both written and verbal, to effectively collaborate with internal teams and present solutions to clients

Technical Requirements:

3-5 years of experience writing and deploying production quality AI models.

Strong hands-on Python programming experience.

Strong experience in AWS including services such as Bedrock, S3, Lambda, SageMaker.

Hands-on technical experience with extensive background in deep learning networks.

In-depth experience in Natural Language Processing (NLP), with a particular emphasis on Large Language Models (LLMs) and Transformer architectures

Strong innovator who understands the nuances of large language models and in-depth hands-on experience working with Amazon Bedrock and foundational LLMs like Claude 3 Sonnet, GPT, LLAMA, Transformer-based architectures or other GPT variants.

Knowledge of model adaptation techniques such as RAG, fine tuning, LoRA, feature engineering, etc.

Proficient knowledge of NLP techniques, including tokenization, language modeling, and embeddings

Experience in data preprocessing, including both structured and unstructured data, for serving AI models.

Strong experience in model fine tuning and performance evaluation

Experience in developing Gen AI applications using LangChain or LlamaIndex Library preferred.

Familiarity with database management systems, such as Pinecone, Weaviate DB, vector search algorithms, and LLM embedding layers preferred.

Published research in the NLP field is highly desirable but not specifically required, indicating an ability to not only understand but also contribute to cutting-edge research.