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Vetted Matplotlib Professionals
Pre-screened and vetted.
Mid-level Machine Learning & Generative AI Engineer specializing in enterprise RAG and MLOps
Junior Machine Learning Engineer specializing in generative modeling and computer vision
Mid-level AI/ML Engineer specializing in Generative AI and RAG systems
Intern AI/ML Engineer specializing in data science, NLP, and reinforcement learning
Mid-level Full-Stack Software Engineer specializing in cloud-native data platforms
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
Mid-level Software Engineer specializing in cloud-native microservices and ML-driven automation
Intern-level Software Engineer specializing in Machine Learning and Full-Stack Web Development
Mid-level Mechanical Engineer specializing in medical robotics and machine learning
Intern Software Engineer specializing in systems, networking, and GPU computing
Junior Marketing Analyst specializing in growth and performance analytics
Senior AI/ML Engineer specializing in GenAI, MLOps, and healthcare analytics
Intern Machine Learning Engineer specializing in LLMs, retrieval, and vision-language models
Principal Data Scientist specializing in AI/ML forecasting and MLOps
Jainum Sanghavi
Mid-level DevOps Engineer specializing in cloud automation and Kubernetes platforms
“Robotics/ML engineer who has built SO(3)-equivariant models for robotic manipulation, including custom equivariant layers and differentiable point-cloud rasterization/derasterization workflows. Also brings 2 years of DevOps experience in banking systems, automating CI/CD and infrastructure at scale (managed 180 OCI servers; reduced rebuild downtime by 80%).”
Swathi Sankaran
Senior Python Full-Stack Developer specializing in cloud, data engineering, and ML/GenAI
“Backend/data engineer with hands-on production experience building FastAPI services on AWS and implementing strong reliability/observability (CloudWatch, ELK, correlation IDs, alarms). Has delivered serverless + container solutions with IaC (CloudFormation/Terraform) and Jenkins CI/CD, and built AWS Glue/PySpark pipelines into S3/Redshift with schema-evolution and data-quality safeguards; demonstrated large-scale SQL tuning (45 min to 3 min on a 500M-row workload).”
Caden Cheah
Intern Full-Stack/ML Engineer specializing in LLM applications and mobile development
“Backend engineer who built a serverless AWS Lambda microservices backend for a parenting assistance mobile app, including a personalized recommendation system optimized to sub-500ms via precomputed scoring and DynamoDB caching. Demonstrates strong production pragmatism: CloudWatch-driven performance tuning (provisioned concurrency), zero-downtime phased schema migrations, and robustness patterns like optimistic locking and request deduplication. Also led a refactor of an LLM RAG pipeline to improve retrieval quality and cut latency from ~5s to ~3s.”
Anurag Patil
Mid-level Data Analyst specializing in machine learning, ETL, and real-world evidence analytics
“Developed and productionized an AI-driven "indication finding" system for AbbVie to identify additional diseases a drug could target, working closely with clinical research teams on cohort inclusion/exclusion criteria and disease rollups. Leveraged an LLM to map clinical inputs to ICD codes and built configuration-driven ML pipelines (Cloudera ML, YAML, scheduled jobs) with structured testing and evaluation for reliability.”
keerthana medaveni
Mid-Level AI/ML Software Engineer specializing in agentic LLM systems
“Built and deployed a production LLM-powered multi-agent compliance copilot (life sciences/finance) using LangChain/LangGraph + RAG over vector databases, delivered via async FastAPI on Kubernetes. Emphasizes audit-ready, deterministic outputs with schema constraints and citations, plus rigorous evaluation/monitoring; reports 60%+ reduction in manual research time and successful production adoption.”
Anvith Reddy Dodda
Mid-level AI Engineer specializing in GenAI, NLP, and MLOps
“LLM/agentic-systems engineer with PayPal experience hardening an LLM-powered fraud support assistant from prototype to production, focusing on low-latency distributed architecture, rigorous evaluation/testing, and security/compliance. Comfortable in customer-facing and GTM contexts—runs technical demos/workshops, builds tailored pilots, and aligns sales/CS with engineering to close deals and drive adoption.”