.png){kind=logo}
Vetted AI & Machine Learning Professionals in the NYC Metro
Pre-screened and vetted in the NYC Metro.
Mid-level AI/ML Engineer specializing in GenAI, NLP, and AWS MLOps
Intern AI/ML Engineer specializing in LLM agents and healthcare data science
Mid-level Applied AI/ML Engineer specializing in scalable generative model infrastructure
Senior AI/ML Engineer specializing in LLMs, RAG, and product-driven AI systems
Staff GenAI Solutions Architect specializing in LLMs, RAG, and AI platforms
Adithya Gururaj
Junior AI Engineer specializing in agentic AI, RAG, and voice/telephony systems
“LLM/agent engineer who has built production multi-agent systems (LangChain/LangGraph) for enterprise workflows like email and calendar automation, with a strong focus on latency, tool-calling accuracy, and evaluation via LangSmith. Also worked on AI long-term memory using knowledge graphs at VEAI and communicated the approach and tradeoffs to CEO/CTO stakeholders.”
David Gil
Senior Technical Artist specializing in game art pipelines, automation, and localization
“Marketing creative/production specialist with experience localizing Facebook ads, marketing emails, and animated billboards for regional markets at Hi5 Games and Tiffany & Co. Has built permutation-based ad templates in Figma for crypto/DeFi marketing (CheatDAO/QiDAO) and produces lightweight motion assets using After Effects/Premiere with optimized encoding workflows.”
Mid-level Machine Learning Engineer specializing in healthcare and financial AI
Lavan Gajula
Mid-level GenAI Engineer specializing in LLM agents and production AI workflows
“Designed and deployed end-to-end LLM-powered AI agent systems to automate knowledge-intensive workflows across marketing/GTM, recruiting, and support. Brings production reliability rigor (evaluation pipelines, monitoring, testing, A/B experiments) plus orchestration expertise (Airflow, Prefect, custom Python) and a track record of translating non-technical stakeholder goals into working AI solutions (e.g., personalized customer engagement agent at Lara Design).”
Sonam Chhatani
Mid-level AI Engineer specializing in causal inference and LLM research
“LLM engineer who has deployed a production system combining LLMs with causal inference (DoWhy) to enable counterfactual “what-if” analysis for experimental research, including a robust variable-mapping/validation layer to reduce hallucinations. Also partnered with non-technical operations leadership at Irriion Technologies to deliver an AI-assisted onboarding workflow that cut onboarding time by 50% and reduced manual errors by ~40%.”
Tarun Gowda
Mid-level Software Engineer specializing in AI, backend systems, and cloud platforms
“Full-stack engineer who helped build and launch an internal genAI platform called GAIL, supporting multiple LLMs, confidential document upload for RAG pipelines, and collaborative chat. Worked across FastAPI, React/TypeScript, AWS/DynamoDB, and Azure, with notable ownership of backend RAG logic, MCP integration architecture, and frontend fixes that improved chat usability.”
Phani Tarun Munukuntla
Junior Machine Learning Engineer specializing in LLMs, NLP, and MLOps
“Developed and productionized VL-Mate, a vision-language, LLM-powered assistant aimed at helping visually impaired users understand their surroundings and query internal knowledge. Emphasizes reliability and safety via confidence thresholds, uncertainty-aware fallbacks, hallucination grounding checks, and rigorous offline + user-in-the-loop evaluation, with experience orchestrating multi-step LLM pipelines (LangChain-style and custom Python async) and deploying on containerized infrastructure.”
Krishna K
Junior Machine Learning Engineer specializing in multimodal systems and LLMs
“Built and productionized a domain-specific LLM-powered RAG knowledge assistant at JerseyStem for answering questions over large internal document corpora, owning the full stack from FAISS retrieval and LoRA/QLoRA fine-tuning to AWS autoscaling GPU deployment. Drove measurable gains (28% accuracy lift, 25% latency reduction) and improved reliability through hybrid retrieval, grounded decoding, preference-model reranking, and Airflow-orchestrated pipelines (35% faster runtime), while partnering closely with non-technical stakeholders to define success metrics and ensure adoption.”
Junior Full-Stack & LLM Application Developer specializing in agentic RAG systems
Mid-level Sonic Arts & Multimedia Editor specializing in audio/video production and design
Mid-level AI/ML Engineer specializing in LLMs, RAG, and AI agents
Junior AI & Machine Learning Engineer specializing in LLM automation and RAG systems
Mid-level AI/ML Engineer specializing in LLM, RAG, and semantic search systems
Mid-level AI/ML Engineer specializing in LLMs, RAG, and agentic AI systems
Mid-level AI Engineer specializing in LLM automation and RAG systems
Priyank Jhaveri
Junior AI/ML & Mobile Engineer specializing in LLMs, synthetic data, and React Native
“Currently at Uplift AI shipping production LLM features that generate personalized growth insights from user reflections using BERT + embeddings + RAG, with strong safety/guardrail practices for sensitive contexts. Also built an end-to-end React Native UGC challenge submission/moderation system that improved repeat submissions and 7-day retention, and has applied rigorous clinical-style evaluation methods on a dental X-ray disease detection project to reduce false negatives.”
“Built a production ad-spend optimization system that combined deterministic audit logic with LLM-generated explanations, surfacing severe inefficiencies including 70-90% wasted spend in some Google Ads accounts. Stands out for pairing measurable business impact with pragmatic AI safety and usability decisions, including approval-gated execution and structured, human-readable recommendations.”