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Vetted Flask Professionals
Pre-screened and vetted.
Mid-level Software Engineer specializing in real-time backend systems and FinTech payments
Mid-level Backend/Distributed Systems Engineer specializing in AWS serverless architectures
Senior Software Engineer specializing in Python, cloud microservices, and conversational AI
Senior AI/ML Engineer specializing in computer vision, NLP, and real-time forecasting
Senior Full-Stack Engineer specializing in FinTech and fraud/risk systems
Senior Software Engineer specializing in cloud platforms for healthcare and e-commerce
Senior Software Engineer specializing in cloud platforms, data pipelines, and ML
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multi-agent systems
Intern Machine Learning Engineer specializing in systems, kernels, and GPU computing
Mid-Level Software Engineer specializing in Ads Serving and Machine Learning Systems
Senior Data Scientist specializing in large-scale ML systems and recommendations
Mid-level AI/ML Engineer specializing in NLP, computer vision, and recommender systems
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.”
Christopher Chu
Senior Backend Engineer specializing in distributed systems and cloud microservices
“Backend/data engineer with experience at Nike building high-volume order orchestration and validation APIs using FastAPI microservices on AWS EKS with Kafka, Redis, and Postgres. Strong in production reliability (timeouts/retries/idempotency), GitOps (Argo CD) + Terraform deployments, and data pipelines (AWS Glue/S3), with hands-on incident ownership and legacy modernization into API-driven services.”
Harish Kasu
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and MLOps
“AI/LLM engineer with production experience at NVIDIA and Microsoft, including building a RAG-based enterprise knowledge assistant that improved accuracy by 42% and scaled to thousands of queries. Deep in inference optimization (TensorRT-LLM, Triton, quantization, speculative decoding) and MLOps/observability (Prometheus/Grafana, MLflow, LangSmith), plus orchestration with Kubeflow/Airflow across multi-cloud.”
Yishi Wang
Junior Machine Learning & Data Science professional specializing in LLMs and analytics
“Amazon internship experience building production GenAI analytics for the returns organization: a multi-agent LLM+RAG system that let analysts query multiple heterogeneous data sources in natural language without hand-written SQL. Also built and operationalized four Apache Airflow DAGs for large-scale ETL, emphasizing observability and freshness-aware metadata to keep outputs accurate and up to date.”
Mid-Level Software Engineer specializing in cloud-native backend systems and FinTech
Senior Full-Stack Engineer specializing in scalable web platforms and AI-driven products
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices
Mid-level AI/ML Engineer specializing in LLMs, RAG, and distributed MLOps
Senior Full-Stack Platform Engineer specializing in scalable cloud systems and AI integrations