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Vetted Neural Networks Professionals
Pre-screened and vetted.
Mid-level Full-Stack Java Developer specializing in microservices and cloud deployments
Mid-level Robotics Engineer specializing in autonomous navigation, SLAM, and perception
Junior Full-Stack Software Engineer specializing in cloud, observability, and web apps
Junior Data Engineer specializing in Azure, ETL, and applied ML
Junior Robotics & Controls Engineer specializing in motion planning and ROS 2
Senior Machine Learning Engineer specializing in LLMs, RAG, and multimodal AI
Mid-level Software Engineer specializing in Python backend systems and APIs
Junior Full-Stack Developer specializing in backend systems and AI search
Intern software engineer specializing in AI, product, and full-stack systems
Intern Data/Software Engineer specializing in APIs, LLM pipelines, and full-stack web apps
Mid-Level Full-Stack Software Engineer specializing in cloud-native web applications
Junior Full-Stack Software Engineer specializing in AWS serverless and Python
Mid-level Data Scientist specializing in GenAI, NLP, and cloud MLOps
Mid-level Machine Learning Engineer specializing in MLOps and LLM/RAG systems
Mid-level Data Scientist specializing in ML, NLP, and forecasting across finance and retail
Intern Game Systems Designer specializing in combat systems and real-time graphics
Ashutosh Khatavkar
Mid-level SDET/Software Engineer specializing in test automation and CI/CD
“AAA game QA professional from Ubisoft (For Honor) with deep live-service multiplayer experience. Known for owning network/competitive integrity risks and building a custom network simulation tool to reliably reproduce desync issues, accelerating debugging and saving 100+ hours. Strong end-to-end QA process skills spanning test planning, triage, regression, and release verification using JIRA/TestRail.”
Sai Manikanta Kasireddy
Mid-level Machine Learning Engineer specializing in cloud-native GenAI and RAG systems
“Built and productionized an internal GenAI chatbot that makes company policy/SOP knowledge instantly searchable, using a secure RAG architecture on AWS (Bedrock/Titan embeddings/OpenSearch Serverless, Textract/Lambda/S3 ingestion, Claude 3 Sonnet). Demonstrates strong MLOps/orchestration experience (Airflow, Step Functions with Lambda/Glue/SageMaker) and a rigorous reliability approach (RAGAS metrics, A/B testing, citation validation, monitoring), including collaboration with compliance stakeholders via review dashboards.”