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Vetted LoRA Professionals
Pre-screened and vetted.
Mid-level Data Scientist specializing in NLP, deep learning, and big data analytics
Mid-level AI/ML Engineer specializing in LLM evaluation, RAG, and GPU-accelerated inference
Senior Data Analytics & Applied ML Engineer specializing in LLMs, RAG, and MLOps
Mid-level AI/ML Engineer specializing in NLP, transformers, and RAG systems
Vignesh Shanmugasundaram
Junior Software Engineer specializing in full-stack development and applied ML
“Full-stack engineer with experience at Zoho and Amazon who has owned production systems end-to-end, including a monolith-to-microservices migration using Kafka and Cassandra that improved search latency ~25% and increased throughput without data loss. Also built a hackathon project (Buildwise) into a sold product for a construction company (AI-driven document compliance checks) and shipped an IoT-based parking availability MVP in 3 weeks.”
Sharath Nyalakonda
Mid-level AI/ML Engineer specializing in NLP, graph models, and MLOps for FinTech and Healthcare
“AI/ML engineer who has deployed production LLM/transformer-based systems for merchant intelligence and fraud/support optimization, delivering +27% merchant engagement and +18% payment success. Deep experience in privacy-preserving, PCI DSS-compliant data/ML pipelines (Airflow, AWS Glue, Spark, Delta Lake) and scalable microservices on Kubernetes, plus proven cross-functional delivery in healthcare claims analytics at UnitedHealth Group (12% HEDIS claim reduction).”
Sarthak Gupta
Mid-level AI/ML Engineer specializing in LLMs, NLP, and real-time AI systems
“Backend engineer who built a real-time pipeline for recording, transcribing, and analyzing audio from 400+ news radio stations, scaling Whisper on an HPC cluster with 7 H100 GPUs. Has strong performance optimization experience (30% latency reduction via SQL/query design; 50% DB call reduction via Redis caching) and has implemented region-based data isolation and PII protections in a regulated environment (JP Morgan Chase).”
Shubham Singh
Mid-level Software Engineer specializing in LLM systems and intelligent search
“Backend engineer from Palantir who built and productionized an enterprise LLM-based document intelligence/search platform, evolving it into a hybrid lexical+vector retrieval system. Emphasizes reliability and cost control via strict LLM gating, robust fallback paths, and evaluation frameworks (e.g., MMLU/BLEU), plus disciplined migration practices (feature flags, dual-writes, shadow reads) to ship changes safely at scale.”
Narasimha Jwalapuram
Mid-level Applied AI Engineer specializing in LLM agents, RAG, and model alignment
“Applied Scientist with legal-tech experience who builds production LLM systems. Created and deployed Quibo AI, a LangGraph-based multi-agent pipeline that turns large markdown/Jupyter inputs into polished blogs and social posts, overcoming context limits via ChromaDB + HyDE RAG. Also built a large-scale iterative code-evolution workflow using multi-model orchestration (GPT/Claude/Gemini) with testing, debugging loops, and evaluation/observability practices.”
Sayak Banerjee
Intern Machine Learning Engineer specializing in LLMs, RAG, and search systems
“Built and shipped production improvements to a Paylocity RAG-based AI assistant, redesigning retrieval into a hybrid HNSW + keyword pipeline and using tuned RRF to fuse rankings—cutting latency by ~2s and reducing token usage by ~5000. Previously spearheaded Apache Airflow integration across ETL pipelines at Acuity Knowledge Partners, creating reusable templates and automated triggers to reduce manual job monitoring.”
Intern AI Engineer specializing in agentic RAG systems and computer vision
Intern Machine Learning Engineer specializing in Generative AI and LLM systems
Mid-level Machine Learning & Data Engineer specializing in MLOps and cloud data platforms
Mid-level AI/ML Engineer specializing in LLMs, agentic systems, and MLOps
Senior Data Scientist specializing in LLM products, voice agents, and FinTech risk modeling
Mid-level Machine Learning Engineer specializing in GenAI, LLM agents, and MLOps
Intern Machine Learning Engineer specializing in NLP and LLM/RAG systems
Senior Client-Facing Solutions Engineer specializing in AdTech and AI integrations
Mid-level Data Scientist specializing in GenAI, NLP, and agentic RAG systems
Principal AI Platform Architect specializing in agentic AI and enterprise LLM infrastructure
Mid-level Generative AI Engineer specializing in LLMs, NLP, and multimodal systems
Rohith Sadanala
Mid-level Machine Learning Engineer specializing in Generative AI and MLOps
“LLM/agent engineer who has shipped production RAG chatbots in sustainability-focused domains, including a packaging recommendation assistant that standardized messy user inputs and used Pinecone-backed retrieval over product/regulatory data. Experienced orchestrating end-to-end ML workflows with Airflow and AWS Step Functions/Lambda, emphasizing reliability (property-based testing, circuit breakers, OpenTelemetry) and measurable performance (latency/cost). Partnered closely with non-technical leadership to ship 3 weeks early, driving adoption by 150+ businesses and ~20% reported waste reduction.”
Ashutosh Choudhari
Mid-level AI/ML Engineer specializing in LLM applications and cloud-native systems
“LLM engineer who has shipped production AI systems, including an RFP requirements extraction platform (OpenAI o4-mini + Azure AI Search + FastAPI) achieving 90%+ accuracy and ~5x throughput through grounding, structured outputs, parallelization, and caching. Also partnered with legal/compliance stakeholders at Nexteer Automotive to deliver an AI document comparison tool with traceability and confidence indicators, adopted by non-technical users and saving ~2 FTEs of review time.”