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Vetted BERT Professionals
Pre-screened and vetted.
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).”
Senior AI/ML Engineer specializing in LLMs, RAG, and multimodal systems
Senior Machine Learning Engineer specializing in LLMs and scalable MLOps
Mid-level AI/ML Engineer specializing in LLMs, NLP, and MLOps
Senior Data Scientist / ML Engineer specializing in LLMs, generative AI, and MLOps
Mid-level Data Scientist / GenAI & ML Engineer specializing in LLM apps and MLOps
Mid-level AI/ML Engineer specializing in LLM infrastructure and FinTech ML platforms
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable MLOps
Mid-level AI/ML Engineer specializing in generative AI, LLMs, and MLOps
Mid-level Software Engineer specializing in backend APIs, data pipelines, and cloud microservices
Mid-level AI/ML Engineer specializing in LLMs, multilingual NLP, and low-latency MLOps
Senior AI/ML Engineer specializing in LLM agents, RAG, and production ML systems
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Machine Learning Engineer specializing in Generative AI and LLM applications
Sai Chandra Bandi
Mid-level AI/ML Engineer specializing in Generative AI, LLM alignment, and RAG
“Built and productionized a real-time enterprise RAG pipeline to improve factual accuracy and reduce LLM hallucinations by grounding responses in constantly changing internal knowledge bases (policies, manuals, FAQs). Experienced in orchestrating end-to-end ML workflows (Airflow/Kubernetes), handling messy multi-format data with schema enforcement (Pydantic/Hydra), and maintaining freshness via streaming incremental embeddings plus batch refresh. Also delivers applied ML solutions with non-technical teams (marketing/CRM) for segmentation and personalized engagement.”
LEQUAN WANG
Intern Applied Scientist / ML Engineer specializing in NLP and conversational AI
“LLM/Conversational AI engineer who built a production multi-turn dialogue system using LoRA fine-tuning on LLaMA, cutting training compute/memory by 90%+ while maintaining low-latency inference via quantization and streaming generation. Experienced in orchestrating end-to-end ML workflows with Prefect/Airflow/Kubeflow (including hyperparameter sweeps and W&B tracking) and improving agent reliability through benchmark-driven testing, shadow-mode rollouts, and stakeholder-informed guardrails.”
Ravikanth Kasamsetty
Executive AI/ML Engineering Leader specializing in cloud-native SaaS and GenAI platforms
“Engineering leader who modernized and unified a fragmented product suite at Milestone via a multi-year cloud-native roadmap, delivering an MVP in three quarters and boosting team velocity by 40% through cross-functional squads. At Prometheum, led a trust-building hybrid architecture (AWS control plane + customer-hosted data plane) using Kubernetes to ensure sensitive enterprise data never left customer networks while remaining cloud-agnostic across providers.”