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Vetted Flask Professionals
Pre-screened and vetted.
Staff Full-Stack Software Engineer specializing in scalable web platforms and cloud infrastructure
Senior Technology Consultant specializing in cloud, data engineering, and AI solutions
Mid-level Generative AI & Machine Learning Engineer specializing in LLMs and RAG
Mid-level Full-Stack Engineer specializing in AI platforms and FinTech
Senior Machine Learning Engineer specializing in LLMs and Generative AI
Senior Backend Engineer specializing in Healthcare & Cloud Platforms
Junior AI Software Engineer specializing in LLM systems and retrieval (RAG)
Senior Software Engineer specializing in AWS distributed systems and developer tools
Mid-level Software Engineer specializing in backend systems, billing, and real-time data pipelines
Intern Full-Stack Software Engineer specializing in distributed systems and cloud services
Mid-level AI/ML Engineer specializing in LLMs, ranking systems, and MLOps
Principal Data Scientist / AI Engineer specializing in healthcare-native AI platforms
Vigynesh Bhatt
Mid-level Software Engineer specializing in backend, cloud, and ML systems
“Software engineer with experience across Goldman Sachs, BYU Broadcasting, Juniper Networks, and an edtech startup (Doubtnut), spanning data migrations, AWS-based media backends, and microservices observability. Built a Redis/ElastiCache caching layer in front of DynamoDB/S3 to improve media delivery latency and cost, and created an SEO indexing automation tool using the Google Search Console API that saved ~15–30 person-hours per day.”
Alexander Choy
Director of AI/ML Engineering specializing in MLOps, data platforms, and 3D computer vision
“Backend/data engineer focused on production ML/LLM systems: built a real-time FastAPI inference API on Kubernetes with strong reliability patterns (timeouts, idempotent retries, centralized error handling). Delivered AWS platforms using EKS + Lambda with GitHub Actions/Helm CI/CD and built Glue-based ETL from S3/Kafka into Snowflake with schema evolution and data-quality controls; also modernized legacy analytics/recommendation workflows into Python services with safe, feature-flagged cutovers.”
Gowri Kajipuram
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multimodal deep learning
“ML/LLM engineer who has built and productionized a large multimodal LLM pipeline end-to-end—fine-tuning a 20B+ parameter model with distributed/FSDP training and deploying on Kubernetes via Triton for ~5x throughput. Strong focus on reliability and safety (monitoring with SHAP, guardrails, A/B testing) with reported ~22% relevance lift and reduced harmful/incorrect outputs, plus experience orchestrating ETL/retraining workflows with Airflow across S3/Snowflake/RDS.”