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Vetted Plotly Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in financial risk, fraud detection, and NLP
Mid-level AI/ML Engineer specializing in forecasting, anomaly detection, and enterprise ML pipelines
Mid-level Full-Stack & AI Engineer specializing in Python, cloud, and LLM applications
Senior AI/ML Engineer specializing in healthcare AI, LLMs, and MLOps
Senior Generative AI & Machine Learning Engineer specializing in LLMs and MLOps
Mid-level AI/ML Engineer specializing in NLP, LLMs, and MLOps in Financial Services
Senior Software Engineer specializing in data platforms, automation, and ML/LLM pipelines
Mid-level AI/ML Engineer specializing in scalable ML systems and cloud MLOps
Mid-level Data Scientist / GenAI Engineer specializing in LLMs, RAG, and MLOps
Principal Data Scientist specializing in Generative AI, LLMs, and ML platforms
Mid-level AI/ML Engineer specializing in recommender systems, NLP, and MLOps
Mid-level AI/ML Data Engineer specializing in analytics, ML pipelines, and LLM applications
Mid-level AI Data Scientist specializing in financial risk, fraud detection, and NLP/LLM systems
Mid-level AI/ML Engineer specializing in MLOps, distributed ML, and RAG pipelines
Senior Data Scientist specializing in Generative AI, NLP, and MLOps
Senior AI Platform Engineer specializing in agentic AI and RAG systems
Senior AI/ML Engineer specializing in GenAI, LLMs, NLP, and MLOps
JYOTHI N
Senior Data Scientist specializing in analytics, experimentation, and BI on AWS
“Data/ML practitioner focused on healthcare data quality and record linkage: analyzed 10M+ records, built anomaly detection and NLP-driven entity resolution, and automated AWS ETL/validation pipelines (Glue/Redshift/Lambda), cutting data errors by 40% and generating $500k in annual savings. Has hands-on experience with embeddings (Sentence Transformers/spaCy), FAISS vector search, and fine-tuning for domain-specific matching.”
Priyanshu Maurya
Mid-level Data Scientist specializing in insurance, finance, and healthcare analytics
“Built and productionized LLM-driven sentiment scoring for earnings call transcripts at Goldman Sachs, replacing legacy NLP to deliver a cleaner trading signal while managing latency/cost via batching, caching, and distilled models. Also implemented an Airflow-orchestrated fraud modeling pipeline at MetLife with drift-based retraining and SageMaker deployment, and has a disciplined evaluation/rollout framework for reliable AI workflows.”