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Vetted Deep Learning Professionals
Pre-screened and vetted.
Mid-level Data Engineer specializing in Azure data platforms and near real-time pipelines
Intern software engineer specializing in full-stack, data engineering, and ML systems
Senior AI/ML Engineer specializing in computer vision, GenAI, and 3D spatial analytics
Senior Machine Learning Engineer specializing in AI, NLP, computer vision, and GenAI
Senior AI/ML Engineer specializing in Generative AI and conversational systems
Junior Software Engineer specializing in full-stack development and ML
Mid-level Data Scientist / ML Engineer specializing in LLMs and predictive analytics
Senior Data Scientist specializing in healthcare analytics and scalable ML pipelines
Mid-level GenAI/ML Engineer specializing in LLMs, RAG, and agentic AI
Senior Machine Learning Engineer specializing in AI systems, LLMs, and MLOps
Mayank Pratap
Intern Robotics Engineer specializing in autonomous navigation and SLAM
“Robotics software engineer with deep ROS2 Humble/Nav2 experience who built an SDF-based navigation system (RRT* global planning + gradient-based local avoidance) and implemented scan-matching localization. Proven real-time performance debugging and optimization on hardware (Unitree B1), including halving compute-cycle latency and resolving ROS2 jitter/message-drop issues through explicit QoS and executor/callback-group design.”
Senior Machine Learning Engineer specializing in MLOps and Generative AI
Mid-level Data Scientist specializing in financial ML, NLP, and MLOps
Mid-level AI/ML Software Engineer specializing in Generative AI and NLP
Executive product and technology leader specializing in AI, data platforms, and cloud transformation
Srijan Dokania
Junior Robotics & Machine Learning Engineer specializing in perception, SLAM, and edge AI
“Built and deployed an Azure-based, fine-tuned CLIP visual retrieval system at Staples for a ~300k-item product catalog, improving edge-case recall by 12% by engineering a custom delta-similarity/dynamic-margin loss. Also has robotics experience using ROS2 for sensor/compute orchestration, including GPS-time-synchronized sensor triggering for robot swarms and latency-bounded optical-flow benchmarking for edge deployment.”
Krishnapriyanka Ponnaganti
Mid-level AI/ML Engineer specializing in agentic AI and production ML systems
“ML/AI engineer with hands-on experience shipping production computer vision and GenAI systems, including a fabric defect detection platform that combined vision models with agentic LLM workflows to reach 89% human-inspector agreement at 200 ms latency. Also built a RAG-based code QA tool for developers and emphasizes production monitoring, evaluation, caching, and reusable Python service design.”
Rithindatta Gundu
Mid-level AI/ML Engineer specializing in LLM systems and cloud MLOps
“Built a production LLM-powered fraud detection platform at Wells Fargo, combining OpenAI/Hugging Face models with RAG-based explanations to make flagged transactions interpretable for risk and compliance teams. Delivered low-latency, real-time inference at high scale on AWS (SageMaker + EKS), with strong observability and security controls, reducing manual reviews and false positives in a regulated environment.”