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Vetted Large Language Models Professionals
Pre-screened and vetted.
Junior Research Engineer specializing in robotics, computer vision, and machine learning
Senior Machine Learning & GenAI Engineer specializing in LLM systems and data pipelines
Senior Applied Scientist specializing in LLMs, GenAI systems, and AutoML
Senior Strategy & Operations Leader specializing in AI and data-driven transformation
Mid-level Machine Learning Engineer specializing in LLMs, ranking, and scalable ML systems
Intern Machine Learning Engineer specializing in optimization, federated learning, and LLMs
Senior AI/ML Engineer specializing in LLMs, RAG, and multimodal recommendation systems
Staff Machine Learning Engineer specializing in LLMs and cloud-native AI platforms
Mid-level Software Engineer specializing in real-time backend systems and FinTech payments
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multi-agent systems
Brian Sanders
Senior Backend Engineer specializing in GenAI, LLMs, and scalable data pipelines
“Backend/ML platform engineer from Snapsheet who owned production Python services and data pipelines for insurance claims, including an AI document classification/summarization FastAPI service on ECS/Fargate processing 1M+ documents/year. Strong in AWS infrastructure (Terraform, CI/CD, secrets/IAM, autoscaling), Glue/PySpark ETL with schema evolution controls, and legacy SAS-to-microservices modernization with safe, feature-flagged rollouts and measurable performance wins.”
Hemant Shukla
Executive AI strategy and product leader specializing in industrial AI and frontier technologies
“25+ year professional exploring entrepreneurship; previously helped develop corporate venture capital at Siemens and AVEVA and ran end-to-end diligence through deal close, with heavy technical diligence on pre-seed/pre-revenue companies. Interested in building an AI-enabled hard lending/origination approach to reduce decision-to-close time and scale in a large lending market, and prefers VC studio/EIR models with paid roles rather than equity-only arrangements.”
Parth Vadera
Senior AI/ML Data Scientist specializing in recommender systems, LLMs, and MLOps
“ML/NLP leader with 12+ years of impact across LinkedIn, TikTok, and Levi's, building and productionizing multimodal recommendation and embedding-based search systems. Deep experience in entity resolution, vector retrieval, and rigorous evaluation, with cloud-native deployment/monitoring (MLflow, Airflow, SageMaker/Lambda, Azure ML, Kubernetes) and demonstrated double-digit relevance gains at millions-of-users scale.”
Santhana Parthasarathy
Executive Engineering Leader specializing in SaaS, Security/Identity, and AI/ML
“Engineering leader (ActiveCampaign, Yalo) with a track record of scaling both systems and orgs: grew an engineering team from 90+ to 200+ (30+ scrum teams) while re-architecting a marketing automation platform from batch to near real-time. Led major infrastructure shifts (RabbitMQ to Kafka, multi-region redundancy) and reports outcomes including 600%+ throughput gains, 99.99% uptime, and business growth from ~80K to 185K customers with revenue surpassing $200M over ~3 years.”
Kusumita Dasgupta
Director-level Engineering Leader specializing in data platforms, cloud systems, and LLM products
“Engineering leader/player-coach with recent hands-on work delivering an agentic AI MVP on Amazon Bedrock (conversational UI + supervisor agent routing between internal knowledge and external sources). Previously drove large-scale data platform cost optimization at Twitter, saving ~$3M–$5M annually, and has owned production incidents end-to-end with a focus on analytics/monitoring improvements and team coaching.”
Harish Kasu
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and MLOps
“AI/LLM engineer with production experience at NVIDIA and Microsoft, including building a RAG-based enterprise knowledge assistant that improved accuracy by 42% and scaled to thousands of queries. Deep in inference optimization (TensorRT-LLM, Triton, quantization, speculative decoding) and MLOps/observability (Prometheus/Grafana, MLflow, LangSmith), plus orchestration with Kubeflow/Airflow across multi-cloud.”
Vinay Ramrupe
Mid AI/ML Engineer specializing in LLM and enterprise generative AI
“ML/AI engineer focused on taking LLM systems from experimentation to reliable production, including enterprise copilot and RAG-based knowledge retrieval use cases. Stands out for combining data pipelines, model training, inference optimization, automated evaluation, and safety guardrails, with cited impact including 20% throughput gains and 30% less manual evaluation effort.”