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Vetted Machine Learning Engineers in the Greater Phoenix
Pre-screened and vetted in the Greater Phoenix.
Junior Machine Learning Engineer specializing in generative modeling and computer vision
Amit Dharam
Junior AI/ML Software Engineer specializing in backend systems and cloud deployment
“Built multiple end-to-end automation and data systems, including an Accio RAG pipeline combining PDF parsing, FastAPI, Neo4j, and vector search, plus Selenium-based scraping for a virtual try-on product. Stands out for reliability-minded engineering: automated testing, structured logging, validation layers, and a data-driven approach to debugging flaky automation that improved CI pass rates to over 98%.”
Mid-level Data Scientist/AI-ML Engineer specializing in LLMs, GenAI, NLP and MLOps
Junior Manufacturing/Industrial Engineer specializing in semiconductor analytics and defect vision
Junior Machine Learning Engineer specializing in robotics and remote sensing
Mid-level AI/Data Engineer specializing in LLMs, RAG pipelines, and cloud data platforms
Mid-level Machine Learning Engineer specializing in LLM, RAG, and conversational AI systems
Mid-level Machine Learning & AI Engineer specializing in LLMOps, digital twins, and RL
DHYAN PATEL
Mid-level AI Engineer specializing in NLP and production ML systems
“AI/LLM engineer who has shipped production RAG chatbots using LangChain/OpenAI with FAISS and FastAPI, focusing on real-world constraints like context windows, concurrency, and latency (reported ~40% latency reduction and <2s average response). Experienced orchestrating AI pipelines with Celery and fault-tolerant long-running workflows with Temporal, and has applied NLP model tradeoff testing (Word2Vec vs BERT) to drive measurable accuracy gains.”
Mid-level Machine Learning Engineer specializing in data and MLOps systems
Junior Backend & ML Engineer specializing in distributed systems and MLOps
Mayank VYAS
Mid-level AI/ML Engineer specializing in LLM agents, RAG retrieval, and IoT ML systems
“Built production LLM-driven products including a job-hunt AI (job ranking + resume optimization) and an InterviewAI agentic pipeline using LangChain. Focused on practical deployment concerns like securing OpenAI usage via rate limiting and tiered quotas, and demonstrates an applied approach to choosing models, retrieval methods (RAG), and prompting strategies.”
Jeevan Hebbal Manjunath
Junior Robotics & Machine Learning Engineer specializing in autonomous systems
“Robotics engineer leading development of a Physical Reservoir Computing controller for a pneumatic soft robotic arm, owning everything from automated data collection and leak-testing automation to hardware design/manufacturing and cross-lab integration with Virginia Tech. Built ROS 2/DDS-based multi-robot systems integrating OptiTrack, a lab quadruped, and a UR5e, and pairs simulation (Gazebo/MuJoCo) + PPO RL training with production-ready tooling (Docker, CI/CD, Flask dashboards, RAG chatbot portfolio).”
Mid-Level Software Engineer specializing in ML and Generative AI applications