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Vetted Machine Learning Engineers in the Austin Metro
Pre-screened and vetted in the Austin Metro.
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.”
Mid-level Machine Learning Engineer specializing in healthcare analytics and MLOps
Mid-level Data Scientist / Machine Learning Engineer specializing in NLP and computer vision
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.”
Mid-level AI/ML Engineer specializing in Generative AI and Azure MLOps
Mid-level AI Engineer specializing in LLM, RAG, and multi-agent systems
Executive AI Architect specializing in low-power edge/embedded AI systems
Mid-level Software Engineer specializing in AI/ML and agentic systems
Vamsi Krishna
Senior Machine Learning Engineer specializing in MLOps and Generative AI
“Built and deployed a production generative-AI copilot at Tungsten that automates invoice/form extraction template creation, reducing weeks of manual model-building work. Combines fine-tuned LLMs (PyTorch/HuggingFace) with OpenCV layout grounding to reduce hallucinations, and runs an end-to-end Kubeflow-based MLOps pipeline with drift monitoring, canary releases, and automated retraining.”