.png){kind=logo}
Vetted Model Monitoring Professionals
Pre-screened and vetted.
Senior Software Engineer specializing in cloud platforms and healthcare AI
Staff Machine Learning Engineer specializing in LLMs and Generative AI
Principal Data Scientist & AI/ML Engineer specializing in LLMs, recommender systems, and MLOps
Mid-level AI/ML Engineer specializing in LLM training, RAG, and scalable inference
Senior AI/ML Engineer specializing in LLMs, recommendation systems, and ML platforms
Senior AI/ML Engineer specializing in LLM applications, RAG systems, and MLOps
Senior Software Engineer specializing in AI infrastructure and distributed systems
Staff Machine Learning Scientist specializing in NLP, LLMs, and Generative AI
Senior Machine Learning Engineer specializing in Generative AI and NLP
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.”
Sudheer Bommichetty
Mid-level Machine Learning Engineer specializing in NLP, MLOps, and Generative AI
“Built and deployed a production LLM conversational AI system at OpenAI supporting chat, summarization, and semantic search at 1M+ requests/day, driving major latency (40%) and accuracy (25%) improvements through Pinecone optimization and tighter RAG with re-ranking. Also has Amazon experience improving recommendation systems by translating ML metrics into business terms to boost CTR and conversions, with strong MLOps/orchestration depth (Airflow, MLflow, SageMaker, Kubeflow).”
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
Senior Software Engineer specializing in Python AI/ML integration and experimentation pipelines
Senior AI/ML Engineering Manager specializing in NLP, computer vision, and MLOps
Senior AI/ML Software Engineer specializing in production ML systems
Senior AI/ML Engineer specializing in Generative AI, RAG, and MLOps for FinTech
Senior AI/ML Engineer specializing in Generative AI and cloud-native platforms
Senior AI/ML Engineer specializing in generative AI and recommendation systems
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).”