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Vetted PySpark Professionals
Pre-screened and vetted.
Senior Full-Stack Engineer specializing in scalable cloud platforms and AI integrations
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps
Senior Full-Stack Engineer specializing in AI/GenAI and cloud-native platforms
Mid-level Software Engineer specializing in real-time backend systems and FinTech payments
Mid-level Machine Learning Engineer specializing in real-time recommender systems and MLOps
Senior Software Engineer specializing in cloud platforms, data pipelines, and ML
Senior Data Scientist specializing in large-scale ML systems and recommendations
Brian Sanders
Senior Backend Engineer specializing in GenAI, LLMs, and scalable data pipelines
“Backend/ML platform engineer from Snapsheet who owned production Python services and data pipelines for insurance claims, including an AI document classification/summarization FastAPI service on ECS/Fargate processing 1M+ documents/year. Strong in AWS infrastructure (Terraform, CI/CD, secrets/IAM, autoscaling), Glue/PySpark ETL with schema evolution controls, and legacy SAS-to-microservices modernization with safe, feature-flagged rollouts and measurable performance wins.”
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and scalable GPU inference
Senior Full-Stack AI/ML Engineer specializing in cloud data platforms and GenAI
Principal Data Scientist specializing in ML, NLP, and forecasting for marketing and supply chain
Senior Python Developer specializing in AI/ML and cloud-native microservices
Staff Software Engineer specializing in commerce, checkout, and payments platforms
Senior Machine Learning Engineer specializing in LLM inference and GPU infrastructure
Mid-level AI/ML Engineer specializing in LLM training, RAG, and low-latency inference
Kowshika M
Mid-level AI/ML Engineer specializing in LLM fine-tuning, inference optimization, and AI safety
“AI/LLM engineer with production experience at NVIDIA, where they fine-tuned and deployed a financial-services chatbot and cut latency ~50% using TensorRT + NVIDIA Triton, scaling via Docker/Kubernetes. Also has consulting experience at Accenture delivering a predictive maintenance solution for a logistics network, bridging non-technical stakeholders with actionable dashboards.”