AI Data Scientist - GenAI / LLM Engineer

Nmk Global Inc.

San Jose, CA, United States

2 months ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

8 years minimum

Working hours

Regular working hours

Job source

dice.com

Tech stack

Artificial Intelligence Amazon Web Services Artificial Neural Networks Django Web Framework Amazon DynamoDB Python (Programming Language) Logistic Regression Machine Learning Natural Language Processing Search Technologies WebSocket Retrieval-Augmented Generation

+13 more

Large Language Models Random Forest Prompt Engineering Generative AI Git Fastapi Kubernetes Deployment Automation Xgboost Machine Learning Operations Api Design Restful APIs Microservices

Job description

We are looking for a highly experienced AI Data Scientist with strong expertise in Generative AI, Large Language Models (LLMs), NLP, Machine Learning, and scalable AI system design. The ideal candidate should have hands-on experience building end-to-end AI/ML solutions, deploying production-grade applications, and working with modern GenAI frameworks and vector databases., < style=”text-align:start; text-indent:0px; -webkit-text-stroke-width:0px; margin-top:8px; margin-bottom:8px”>Generative AI / LLM Technologies:

Strong Python programming expertise
Hands-on experience with:
LangChain
LangGraph
RAG (Retrieval-Augmented Generation)
RAGAS
LangSmith
DeepEval
Strong understanding of:
Semantic Search
Reranking techniques
Vector Databases
Prompt Engineering
LLM Tool Calling / Function Calling
Experience evaluating and optimizing LLM performance and AI pipelines

< style=”text-align:start; text-indent:0px; -webkit-text-stroke-width:0px; margin-top:8px; margin-bottom:8px”>NLP (Natural Language Processing):

BERT
SBERT
Transformers
Word2Vec
GloVe
FastText
RNNs / LSTMs
DIET Classifier (RASA)

< style=”text-align:start; text-indent:0px; -webkit-text-stroke-width:0px; margin-top:8px; margin-bottom:8px”>Machine Learning:

XGBoost
Random Forest
Gradient Boosting Models (GBM)
Neural Networks
Logistic Regression
Time Series Models

< style=”text-align:start; text-indent:0px; -webkit-text-stroke-width:0px; margin-top:8px; margin-bottom:8px”>Engineering & Deployment:

Django
REST APIs
FastAPI
WebSockets
Microservices Architecture
Kubernetes
Helm
Git
AWS Services including:
DynamoDB
OpenSearch

Requirements

Strong experience with Vector Databases
Experience building APIs and Microservices
Ability to design standalone scalable AI systems and architecture
Proven experience delivering end-to-end implementations in production environments
Strong communication and problem-solving skills, * 8+ years of overall industry experience
Strong background in AI/ML production systems
Experience working in enterprise-scale environments
Ability to explain architecture, workflows, and deployment strategies clearly during discussions/interviews