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Vetted AI & Machine Learning Professionals in the Bay Area
Pre-screened and vetted in the Bay Area.
Popular Titles
Senior AI/ML Engineer specializing in applied AI and scalable backend systems
Senior AI Engineer specializing in LLMs, RAG, and production ML systems
Staff AI Systems Engineer specializing in LLM platforms and distributed systems
Mid-level AI/ML Engineer specializing in LLM training, RAG, and scalable inference
Staff AI/ML Engineer specializing in LLMs, fraud detection, and MLOps
Esha Pahwa
Intern Machine Learning Engineer specializing in LLM agents and multimodal reasoning
“LLM/agent engineer who built a production code-generation agent at Corvic AI that lets non-technical users query CSV/tabular data in natural language by generating and executing Python. Focused on making LLM systems reliable and scalable via schema-aware validation, sandboxed execution-feedback retries, prompt caching/embeddings, async execution, and high-throughput data processing with Polars; also partnered with Adobe product/marketing to ship brand-aligned AI content generation for email and push notifications.”
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 Engineer specializing in recommender systems, GenAI, and applied ML
Senior Machine Learning Engineer specializing in NLP and Generative AI
Staff ML Platform Engineer specializing in distributed training and inference
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.”
Vishanth Iyer
Senior AI/ML Engineer specializing in LLMs, multimodal AI, and scalable MLOps
“ML/NLP engineer with experience at NVIDIA and Cruise building production-grade AI systems across genomics/biomedical research and autonomous vehicle data. Has delivered multimodal LLM pipelines, large-scale entity resolution, and hybrid semantic search (BERT embeddings + FAISS + Elasticsearch), with measurable impact (≈40% accuracy/retrieval gains; ≈30% data consistency improvement) and strong MLOps practices (Kubernetes, CI/CD, MLflow, Prometheus/Grafana).”
Senior AI/ML Engineer specializing in LLMs, RAG, and multimodal systems
Senior Machine Learning Engineer specializing in LLMs and scalable MLOps
Senior Research Scientist specializing in LLM verification and fraud/risk modeling
Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable MLOps
Senior AI/ML Engineer specializing in LLM agents, RAG, and production ML systems
Ronald Nap
Intern Machine Learning & AI Engineer specializing in computer vision and ML systems
“Robotics/ML engineer with internship experience at Valeo building a deep-learning prototype to replace parts of a legacy SLAM backend for autonomous parking, focused on making models run reliably in real time on embedded hardware (quantization/distillation + TensorRT). Also brings strong MLOps/deployment experience (Docker, Kubernetes on AWS EKS, CI via GitHub Actions) and has supported patent filing by explaining the technical approach to legal stakeholders.”
Subhash Mothukuru
Mid-level Machine Learning Engineer specializing in LLMs, generative AI, and MLOps
“Built and shipped a production LLM-powered medical scribe that generates structured clinical visit summaries using RAG, strict JSON schemas, and post-generation validation to reduce hallucinations. Experienced in making LLM workflows deterministic and observable (structured logging/metrics/tracing) and in evaluation-driven iteration with metrics like schema pass rate and edit rate; collaborated closely with clinicians and policy stakeholders at Scale AI to drive adoption.”
Sahil Bansal
Mid-level Backend & ML Engineer specializing in LLM systems and scalable AI pipelines
“Built and shipped a real-time AI phone agent for small businesses that handles bookings/FAQs/messages using streaming ASR, an LLM with tool-calling, and TTS; deployed to production for multiple paying customers. Demonstrates strong applied LLM reliability practices (tool-first grounding, retrieval, hard-negative testing, and production monitoring) and experience orchestrating multi-step AI workflows with Airflow, Prefect, and AWS Step Functions.”
Junior Quantum/AI Research Engineer specializing in quantum simulation and LLM alignment