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Vetted MLflow Professionals
Pre-screened and vetted.
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
Mid-level Data Scientist specializing in Generative AI and LLM applications
Principal Data Scientist specializing in Generative AI and security analytics
Staff ML Platform Engineer specializing in distributed training and inference
Senior AI/ML Engineer specializing in generative AI and recommendation systems
Senior Full-Stack AI Engineer specializing in generative AI and cloud platforms
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).”
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).”
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.”
jagadeshwar nomula
Executive Technology Leader (CTO) specializing in AI, Search, Cloud, and Edge computing
“Founder building an enterprise agentic AI startup who has already raised about $100K (friends & family plus self-funding). Has prior and current experience engaging VCs (including outreach to both large and small firms) and emphasizes demo-driven pitching, enterprise customer validation, and targeting billion-dollar market opportunities.”
Executive Technology & Data Leader specializing in AI, cloud modernization, and digital strategy
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
Senior Research Scientist specializing in LLM verification and fraud/risk modeling
Mid-level Data Scientist / GenAI & ML Engineer specializing in LLM apps and MLOps