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Vetted PySpark Professionals
Pre-screened and vetted.
Kevin Lee
Senior Software Engineer specializing in scalable backend and platform systems
“Backend/data engineer with hands-on production experience across GCP (FastAPI microservices on Kubernetes) and AWS (Lambda, ECS Fargate, Glue). Has modernized legacy SAS batch systems into Python services with parallel-run parity validation, and has strong operational rigor in ETL reliability/monitoring plus proven SQL tuning impact (25s to <300ms, ~60% CPU reduction).”
Subhash Mothukuru
Mid-level Machine Learning Engineer specializing in LLMs, generative AI, and MLOps
“Built and shipped a production LLM-powered medical scribe that generates structured clinical visit summaries using RAG, strict JSON schemas, and post-generation validation to reduce hallucinations. Experienced in making LLM workflows deterministic and observable (structured logging/metrics/tracing) and in evaluation-driven iteration with metrics like schema pass rate and edit rate; collaborated closely with clinicians and policy stakeholders at Scale AI to drive adoption.”
Marcos Lopez
Senior Full-Stack Engineer specializing in cloud-native web apps and data pipelines
“Backend/data engineer with healthcare/telehealth domain experience, building patient appointment and data-processing systems on AWS. Has delivered production microservices and ETL pipelines (Flask/Celery, Glue/PySpark) with strong reliability/observability practices (JWT, retries/timeouts, Sentry/CloudWatch) and modernization experience migrating SAS workflows to Python services, including a documented 10min→30sec SQL performance win.”
Jayashree Raman
Director-level Data Architecture & Governance leader specializing in cloud analytics platforms
“Technology/architecture leader with Accenture experience delivering data- and AI/ML-driven products, including a legal contract search solution and customer sales analytics for AWS. Known for scaling distributed teams (onshore/offshore), making pragmatic architecture decisions, and solving hard data problems (proprietary sources, data quality) while implementing scalable integrations like Redshift-to-Salesforce via parallelized pipelines.”
Junior Software Development Engineer specializing in Android, cloud automation, and IoT/ML
Mid-level Full-Stack Python Developer specializing in FinTech and ML-driven automation
Mid-Level Software Engineer specializing in Python backend and ML infrastructure
Junior Software Development Engineer specializing in AI agents and personalization
Intern Machine Learning Engineer specializing in NLP and search
Junior Machine Learning Engineer specializing in LLMs, data pipelines, and MLOps
Mid-level AI/ML Engineer specializing in GPU-accelerated LLMs, RAG, and production MLOps
Intern Machine Learning & Cloud Engineer specializing in cloud-native deployment and forecasting
Mid-level Machine Learning Engineer specializing in MLOps and cloud-native ML systems
Mid-level AI/ML Engineer specializing in LLMs, RAG pipelines, and multi-agent systems
Senior Data Scientist specializing in NLP, LLMs, and Generative AI automation
Senior Agentic AI & Backend Engineer specializing in LLM platforms and multi-agent systems
Junior AI/ML Engineer specializing in LLM agents, RAG, and multimodal data pipelines
Senior Backend/Platform Engineer specializing in Python, Kubernetes, and data streaming
Senior Applied Scientist specializing in LLMs, GenAI systems, and AutoML
Mid-level Machine Learning Engineer specializing in LLM personalization and scalable MLOps