.png){kind=logo}
Vetted SHAP Professionals
Pre-screened and vetted.
Mid-level Machine Learning Engineer specializing in NLP, LLMs, and MLOps
Mid-level AI/ML Engineer specializing in GenAI, LLMs, and real-time ML systems
Mid-level AI/ML Engineer specializing in GenAI, RAG, and cloud-native ML platforms
Mid-level AI Data Scientist specializing in financial risk, fraud detection, and NLP/LLM systems
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.”
Manish Mallikarjuna Devatha
Principal Applied Scientist specializing in ML systems and Generative AI
“Built and owned an end-to-end agentic RAG chatbot platform for Baptist Health that helped clinicians access policy and clinical documents faster, reducing manual lookup by 80% and delivering about $2M in annual savings. Brings strong healthcare GenAI production experience, including HIPAA-aligned governance, PHI redaction, observability, evaluation, and scalable Python/Kubernetes deployment practices.”
“Built and deployed a production RAG-based LLM Q&A and summarization platform for internal documents, emphasizing grounded answers with structured prompting and citations to reduce hallucinations. Experienced orchestrating end-to-end LLM workflows with LangChain plus cloud pipelines (Azure ML Pipelines, AWS), and runs iterative evaluation using both metrics (accuracy/hallucination/latency/cost) and real user feedback to drive reliability.”
Haider Shah
Principal AI/ML Architect specializing in GenAI, LLMs, RAG, and Agentic AI
“FinTech/AI engineer who has shipped an end-to-end discrepancy-detection product for financial managers using Next.js, FastAPI/GraphQL, Pinecone, and AWS (with dev/staging/prod, observability, A/B testing, and documentation). Also built an AI-native “AI Genesis” system with agentic cyclic workflows, routing, and tool use, and has experience modernizing legacy systems via the strangler fig pattern while coordinating with senior stakeholders on a 5G autonomous simulation platform.”
Pratik Jaiswal
Mid-level AI/ML Engineer specializing in financial services ML and MLOps
“ML engineer/data scientist with M&T Bank experience who built a production reinforcement-learning portfolio analytics tool for wealth management, emphasizing near real-time performance via batch/serving separation and robust generalization through stress-scenario backtesting and RL regularization. Strong MLOps background (Airflow, Grafana, MLflow) and proven ability to drive adoption with non-technical stakeholders using KPI alignment and SHAP-based explanations.”
Mid-level Machine Learning Engineer specializing in MLOps and applied AI
Mid-level Machine Learning & Generative AI Engineer specializing in enterprise RAG and MLOps
Mid-level AI/ML Engineer specializing in NLP, MLOps, and compliance-focused ML systems
Intern AI/ML Engineer specializing in data science, NLP, and reinforcement learning
Intern AI/Data Science Engineer specializing in LLM agents, data engineering, and predictive analytics
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and RAG for financial services
Mid-level Machine Learning Engineer specializing in NLP, recommender systems, and MLOps