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Vetted pandas Professionals
Pre-screened and vetted.
Principal Machine Learning Scientist specializing in GenAI, LLMs, and RAG
Mid-level Data Scientist specializing in ML for healthcare and strategy analytics
Senior Applied AI Engineer specializing in LLMs, NLP, and production AI systems
Senior Python Developer specializing in AI/ML and cloud-native microservices
Senior Full-Stack Engineer specializing in cloud, real-time data, and web platforms
Mid-level Software Engineer specializing in ML-driven software testing and developer tools
Senior Software Engineer specializing in cloud platforms, healthcare imaging, and scalable APIs
Mid-level Software Engineer specializing in backend, ML platforms, and FinTech
Senior Full-Stack Software Engineer specializing in Telehealth and FinTech
Mid-level Software Engineer specializing in Python, distributed systems, and AI backend services
Senior Machine Learning Engineer specializing in LLM inference and GPU infrastructure
Mid-level AI/ML Engineer specializing in FinTech risk and fraud systems
Mid-Level Software Development Engineer specializing in AWS serverless and ML/GenAI
Mid-level Machine Learning Engineer specializing in generative AI, NLP, and MLOps
Senior Machine Learning Engineer specializing in GenAI, NLP, and recommendation systems
Sumer Joshi
Senior Full-Stack Engineer specializing in backend systems and AI applications
“Candidate is deeply focused on AI-native software development, using a deliberate planner/implementer agent workflow with tools like Cursor, Claude, and Kimi. They also built a personal project called Config Proctor, an AI-agent-driven Terraform/AWS self-healing system that identifies infrastructure configuration gaps and proposes fixes.”
Christopher Bun
Executive AI/ML technology leader specializing in healthcare, biotech, and legal AI
“Repeat founder and startup advisor with experience spanning academic, health tech, legal tech, sports, and gaming. Has participated in fundraising and due diligence and has built companies, engineering teams, and software platforms from scratch, with a strong product-design-first approach to product-market fit and market selection.”
Kenil Tanna
Staff-level Machine Learning Engineer specializing in LLMs and MLOps for Financial Services
“Machine learning/NLP practitioner at J.P. Morgan who led development of a production RAG system and an entity resolution pipeline for complex financial data. Deep hands-on experience with embeddings (Sentence-BERT), vector search (FAISS/pgvector), LLM fine-tuning (LoRA/PEFT), and rigorous evaluation (human-in-the-loop + A/B testing) backed by strong MLOps on AWS (Docker/Kubernetes, MLflow, Prometheus/Datadog).”
Prahlad Vivek
Intern Robotics Engineer specializing in robot learning, SLAM, and control
“Robotics architect intern/new-grad focused on warehouse AMRs, building ROS2 sensor-fusion and SLAM stacks (FastSLAM-style particle filter) and validating in Gazebo with ground-truth metrics. Also interned at ASML debugging real-time in-vacuum robot behavior via Python state-machine telemetry scripts, identifying a firmware driver issue impacting throughput.”
Sahil Sinha
Mid-Level Software Engineer specializing in full-stack development, cloud, and data infrastructure
“Software engineer at Fannie Mae (~3 years) working on high-volume loan data pipelines using AWS (SQS/S3), Java listeners, Postgres, and Python/SQL-based data quality validation. Also built a chess data collection system (leveraging experience as an International Master) with robust retry/monitoring, schema-change handling, and idempotent backfills to prevent bad data from reaching downstream systems.”
Ziwen Shen
Junior Machine Learning Engineer specializing in computer vision, reinforcement learning, and PINNs
“ML/Simulation engineer who productionized a Multi-Agent Reinforcement Learning system for 30+ firms at Belt and Road Big Data Company, integrating research code into an enterprise backend via Dockerized deployment and scalable data pipelines on GCP/Vertex AI. Demonstrated strong production debugging by tracing apparent network timeouts to hardware memory exhaustion caused by software state-history garbage collection issues, and built custom reward functions to model complex market dynamics (entry/exit, pricing).”
Nikhil Reddy
Mid-level AI/ML Engineer specializing in GPU inference and LLM platforms
“Built and deployed an LLM-powered platform that turns models into scalable REST/gRPC APIs, focusing on keeping GPU-backed inference fast and stable during traffic spikes. Experienced with AWS orchestration (EKS/ECS/Step Functions), safe model rollouts, and production-grade monitoring/testing for reliable AI agents and workflows.”