What are the responsibilities and job description for the Gen AI Engineer / AI ML Engineer position at Atlantis IT group?
Job Description
Job Description
Title : Gen AI(Health Care Domain)
Remote
Visa : Only USC, GC
Responsibilities :
GenAI Pipeline Development :
o Design and implement Generative AI pipelines for Chat, RAG, and Fine-tuning applications.
o Collaborate with cross-functional teams to refine models based on user feedback.
Model Performance Evaluation :
o Establish metrics for assessing GenAI module performance and accuracy.
o Implement quality assurance processes to validate outputs before deployment.
Model Deployment and Maintenance :
o Ensure smooth deployment of GenAI models, collaborating with the team for effective performance.
o Set up monitoring protocols to evaluate model performance post-deployment.
Documentation and Integration :
o Maintain clear documentation for processes and models to facilitate team accessibility.
o Ensure seamless integration of GenAI solutions with existing systems and workflows.
Research and Innovation :
o Stay updated on Generative AI trends and contribute to innovative solutions.
o Evaluate state-of-the-art developments to implement into novel technologies.
Skills Needed :
Technical Expertise :
o Strong experience with Small / Medium / Large Language Models (e.g., GPT-4, BERT, LLAMA) and GenAI
pipelines.
o Proficiency in retrieval-augmented generation systems and orchestrator agents / LLM chains.
Programming and Tools :
o Advanced proficiency in Python.
o Experience with Git and Jira for development and task management in an active project setting.
Cloud and Document Management :
o Experience with Azure Blob or AWS S3 and document management integration.
o Skills in PDF parsing, document segmentation, and handling various content types.
Database and Analytical Skills :
o Experience with vector and relational DBs (e.g PGvector, Weaviate, etc), and vector search algorithms.
o Strong problem-solving abilities for project evaluation criteria.
Communication :
o Excellent verbal and written communication skills for effective collaboration.
Topics where people did not do enough elaboration in past Interview!!
Partitioning
Depending too much on large context machines
Chunking vs large context
Do you not have much experience in chunking and partitioning
Evaluation - metrics
ROUJE
Daily U
RAGAS
Classics - f1precision and accuracy and recall
Pipeline that ingests everything
If they don't have the strongest engineer, they can teach
Data preprocessing
What type of data
How are you extracting it - havent heard that
Whats chunking strategy
Retreival and chat generation - how are you evaluating retreieval
Hallucinations
Finetuning
Have to understand machine learning
