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Vetted Python Developers in Texas
Pre-screened and vetted in Texas.
Senior Data/GenAI Engineer specializing in cloud-native ML, RAG, and real-time data platforms
Sahithi S
Mid-level AI/ML Engineer specializing in NLP, MLOps, and Generative AI
“Built and deployed a production generative AI chatbot at NVIDIA using LangChain + GPT-3 integrated with internal data sources, cutting response time nearly in half and improving CSAT by ~12 points. Also delivered LLM-driven QA tools by fine-tuning Hugging Face transformer models and deploying via an AWS-based pipeline (Lambda/Glue/S3) with orchestration (Airflow/Step Functions), CI/CD, Kubernetes, and monitoring (MLflow/Splunk/Power BI).”
Senior Python/ML Engineer specializing in LLM-powered backend systems
“LLM/agent workflow engineer with healthcare experience (CVS/CBS Health) who built and deployed a production call-insights platform using Azure OpenAI + LangChain/LangGraph, including sentiment and compliance checks. Demonstrates deep HIPAA/PHI handling (tenant-contained processing, redaction, RBAC/encryption/audit logging) and production rigor (testing, eval sets, validation/retries, autoscaling) to scale to thousands of transcripts.”
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and multi-agent systems
Senior Machine Learning Engineer specializing in LLMs and scalable AI platforms
Senior Generative AI Engineer and Data Scientist specializing in enterprise ML and RAG systems
Mid-level Full-Stack Python Developer specializing in FinTech and real-time payments
Dharanidharan Loganathan
Senior Python Developer specializing in data engineering, MLOps, and cloud platforms
“Backend/data engineer with production experience building secure Django/DRF APIs (JWT RS256 + rotating refresh tokens), background processing with Celery, and strong reliability practices (timeouts, retries/backoff, structured logging, audit trails). Has delivered AWS solutions spanning Lambda + ECS with IaC/CI-CD and built Glue/PySpark ETL pipelines with schema evolution and data-quality quarantine patterns; also modernized a legacy SAS pipeline to Python/PySpark with parallel-run parity validation and phased rollout.”
Senior Generative AI Engineer specializing in LLM applications and cloud-native AI platforms
Mid-level Full-Stack Python Developer specializing in cloud microservices and ML
Mid-Level Python & GenAI Developer specializing in LLM chatbots and RAG
Tejaswini P
Mid-level Machine Learning Engineer specializing in NLP, LLMs, and MLOps
“Built and deployed an LLM-powered financial/regulatory document analysis platform at State Street, combining fine-tuned transformer models with a RAG pipeline over internal knowledge bases. Owned the productionization stack (FastAPI, Docker, SageMaker, Terraform, CI/CD) plus monitoring for drift/latency/hallucinations, delivering ~40% faster analyst review and improved reliability through chunking/embeddings and grounding.”
Nandini Reinthala
Mid-Level Full-Stack Python Developer specializing in AI and data platforms
“Full-stack engineer who builds TypeScript/React SPAs on Python (Flask/FastAPI) backends and has hands-on experience integrating AI components (Azure OpenAI, LangChain, vector databases) into user workflows. Has built internal AI-enabled dashboards/search tools for analysts and business users, emphasizing typed API contracts, CI/CD-driven quality, and microservices reliability patterns (monitoring, retries, idempotency) at scale.”
Mid-level Python Developer specializing in cloud-native microservices on AWS
Mid-level AI/ML Engineer specializing in Generative AI and cloud-based ML systems
Mid-level Python Developer specializing in AWS cloud-native backend systems
Mid-level Applied AI Engineer specializing in Generative AI and RAG systems
Siva Pothuru
Mid-level AI/ML Engineer specializing in LLMs, MLOps, and cloud-native ML
“LLM/agent engineer at USAA who built a production GPT-4o RAG conversational assistant for financial analysts, focused on regulatory interpretation and internal documentation search. Emphasizes compliance-grade reliability with strict grounding, safe fallbacks, and full auditability via MLflow/DVC plus human-in-the-loop review; reports ~45% reduction in ticket resolution time.”
Aravind Gudipudi
Mid-level AI/ML Engineer specializing in MLOps and cloud-deployed ML systems
“ML/AI engineer who built and productionized an NLP system at PurevisitX, orchestrating end-to-end ML workflows with Airflow (S3 ingestion through auto-retraining) and optimizing for drift and low-latency inference. Also partnered with Citibank risk teams on a fraud detection model, translating results via dashboards and iterating thresholds based on stakeholder feedback.”