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Vetted Sentiment Analysis Professionals
Pre-screened and vetted.
Executive growth and brand strategy leader specializing in technology and GTM transformation
Principal Data Scientist & AI/ML Engineer specializing in LLMs, recommender systems, and MLOps
Staff Data Scientist specializing in machine learning, deep learning, and big data
Mid-level AI/ML Engineer specializing in LLM training, RAG, and scalable inference
Staff Machine Learning Scientist specializing in NLP, LLMs, and Generative AI
Farabi Hassan
Principal Product Leader specializing in AI-powered enterprise and marketplace platforms
“Product leader with experience at Zillow, Amazon, and Chewy, focused on high-scale ML and UX-driven product improvements. Has led end-to-end rebuilds and launches that delivered measurable business impact, including a 23% conversion lift in lead routing, 40%+ reduction in delivery-related customer contacts, and 10%+ ecommerce conversion gains.”
Christopher Sipola
Senior Machine Learning Engineer specializing in LLMs and recommendation systems
“ML/GenAI engineer who owned major parts of Spotify’s AI DJ from offline experimentation through deployment, monitoring, and iteration. They combine recommender systems, RAG, real-time feedback loops, and LLM safety/orchestration to ship consumer-facing personalization features that drove double-digit engagement and deeper listening sessions.”
Somya Upadhyay
Senior Software Engineer specializing in cloud infrastructure and large-scale data pipelines
“Backend engineer on Amazon’s Geospatial Data team (Amazon Maps) who built a real-time road-layer service ingesting third-party and internal signals to deliver road closures/traffic overlays to delivery drivers on a ~3-minute cadence while minimizing mobile data egress. Demonstrates strong production reliability skills (rate limiting, idempotency, cache stampede prevention) and security depth (IAM, RBAC, tenant row-level security), plus careful handling of edge cases like manual override protection against automated feed overwrites.”
Pradeep Nadella
Mid-level AI/ML Engineer specializing in LLM optimization and real-time fraud/risk modeling
“ML engineer with 5 years at Stripe building and productionizing real-time fraud detection at massive scale (3M+ transactions/day; $5B+ annual payment volume). Delivered measurable impact (22% accuracy lift, 18% loss reduction, +3–5% authorization rates) and has strong MLOps/orchestration experience (Docker, Kubernetes, Airflow, MLflow, CI/CD, monitoring/rollback) plus a structured approach to LLM agent/RAG evaluation.”
Mid-level AI/ML Engineer specializing in LLM training, RAG, and scalable inference
Staff AI Full-Stack Engineer specializing in LLMs, multi-agent systems, and Voice AI
Senior AI/ML Engineering Manager specializing in NLP, computer vision, and MLOps
Senior AI/ML Engineer specializing in LLMs, RAG, and multimodal systems
Senior AI/ML Engineer specializing in Generative AI, RAG, and MLOps for FinTech
Executive Founder-Operator specializing in AI-native products, operations, and GTM
Mid-level Data Scientist specializing in Generative AI and LLM applications
Mid-level AI/ML Engineer specializing in Generative AI and multilingual NLP
Tolulope Akinlabi
Mid-level Cyber & Cloud Security Analyst specializing in AI/ML and cloud risk
“Built a production AI security compliance assessment system using the OpenAI API that ingests company policy documents, performs RAG over embeddings stored in Supabase/FAISS, and generates executive-level gap and maturity reports mapped to NIST CSF, SOC 2, and PCI DSS. Also developed a multi-agent trading assistant orchestrated with LangChain, combining live market data (Yahoo/Polygon.io), sentiment/technical indicators, LSTM-based forecasting, and LLM-generated recommendations.”
Jayaprakash Majji
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and scalable inference
“ML/LLM engineer who built and shipped an LLM-powered internal knowledge assistant at Meta, focusing on production-grade RAG to reduce hallucinations and improve trust. Deep experience with scaling and serving (FSDP/DeepSpeed/LoRA, Triton, Kubernetes autoscaling) and reliability practices (Airflow retraining, MLflow versioning, monitoring with rollback), including sub-100ms latency and ~35% GPU memory reduction.”
Brian Gomez
Senior Machine Learning Engineer specializing in AI/ML, NLP, and computer vision
“McKinsey & Company ML/NLP practitioner who builds production-grade AI systems across sectors (notably healthcare and finance), including RAG/LLM solutions, entity resolution pipelines, and embedding-powered search with vector databases. Demonstrated measurable impact (40% reduction in data duplication) and strong MLOps/data workflow practices (Airflow, MLflow, Spark, AWS/GCP, Prometheus, CI/CD).”
Vijay Khera
Principal Product Leader specializing in SaaS, cloud, and AI platforms
“Senior enterprise product leader with high-impact experience at AWS and SirionLabs, spanning AI-powered database migration and NLP-driven contract analytics. Stands out for shipping trustworthy human-in-the-loop AI products with measurable business impact, including a GA launch that lifted automated schema conversion to 90%+ and drove ~20% downstream revenue growth, plus a rapid COVID-era CLM solution that produced upsell and cross-sell gains.”
Deepak Guntreddi
Mid-level Full-Stack Developer specializing in Java/Spring Boot and React
“NVIDIA engineer who built and shipped a production LLM-powered enterprise knowledge system (summarization, transcription, and Q&A) that cut document retrieval time ~30%. Deep hands-on experience with RAG (FAISS/Pinecone), GPU-accelerated microservices on AWS, and reliability/safety practices (Guardrails AI, prompt A/B testing, canary releases) plus strong MLOps orchestration across Airflow, Step Functions, and Kubernetes GitOps.”