.png){kind=logo}
Vetted MLflow Professionals
Pre-screened and vetted.
Mid-level AI/ML Data Engineer specializing in data pipelines, MLOps, and LLM/RAG systems
Mid-level Machine Learning Engineer specializing in MLOps and scalable ML pipelines
Mid-level AI/ML Engineer specializing in multimodal and generative AI at scale
Mid-level AI/ML Engineer specializing in NLP, transformers, and RAG systems
Mid-level AI/ML Engineer specializing in LLMs, RAG, and enterprise AI
Senior Data/GenAI Engineer specializing in cloud-native ML, RAG, and real-time data platforms
Mid-level AI/ML Engineer specializing in recommendation, retrieval, and MLOps
Mid AI/ML Engineer specializing in LLM systems and inference optimization
Senior AI Infrastructure & Backend Engineer specializing in LLM systems
Senior AI Infrastructure Engineer specializing in LLM systems and real-time ML platforms
Surya Singh
Mid-level AI/ML Engineer specializing in FinTech and fraud detection
“ML/backend engineer with PayPal experience building high-stakes production systems, including a GenAI internal support assistant and a real-time fraud scoring pipeline. Strong in Python/FastAPI, model-serving infrastructure, RAG architecture, and production observability, with clear readiness to transition those backend patterns into a TypeScript stack.”
Sharath Nyalakonda
Mid-level AI/ML Engineer specializing in NLP, graph models, and MLOps for FinTech and Healthcare
“AI/ML engineer who has deployed production LLM/transformer-based systems for merchant intelligence and fraud/support optimization, delivering +27% merchant engagement and +18% payment success. Deep experience in privacy-preserving, PCI DSS-compliant data/ML pipelines (Airflow, AWS Glue, Spark, Delta Lake) and scalable microservices on Kubernetes, plus proven cross-functional delivery in healthcare claims analytics at UnitedHealth Group (12% HEDIS claim reduction).”
Justin Turner
Executive Technology Leader (CTO/CIO/CISO) specializing in cloud, security, and data platforms
“CTO-level technology leader with experience building end-to-end tech strategy and roadmaps, modernizing legacy environments in healthcare (GenesisCare), and scaling engineering into large global teams (Amadeus). Built a DevOps organization at Syniverse for the Visibility Suite, implementing Kubernetes/Terraform/Chef automation that drove ~75% faster deployments, and is known for staying hands-on (including data center work) while leading strategically.”
Sriram Rajaraman
Senior Infrastructure Platform Architect specializing in Kubernetes and hybrid cloud
“Platform/infra engineer with strong ownership of Kubernetes on VMware and day-to-day hybrid on-prem-to-AWS operations. Has hands-on experience automating infrastructure delivery with Terraform/Ansible/CI-CD, and has resolved real production issues spanning CSI storage reattachment during upgrades, vSphere storage-latency performance degradation, and hybrid connectivity/routing failures with improved validation, monitoring, and failover.”
Gagan Mundada
Intern Machine Learning Engineer specializing in multimodal AI and evaluation benchmarks
“ML-focused candidate with beginner ROS/ROS2 experience (custom pub-sub nodes; TurtleBot3 SLAM simulation debugging via topic inspection and transform/orientation checks). Has research/project exposure to LLM training approaches (GRPO with pseudo-labels using Hugging Face TRL on Qwen/Llama) and uses Docker/Kubernetes + CI/CD to run ViT saliency-attention/compression workloads on UCSD Nautilus infrastructure.”
Abhay Murjani
Director-level Data Science Manager specializing in ML forecasting, experimentation, and MLOps
“Data/ML engineer with experience at American Express and Amazon, owning an end-to-end rewards redemption/liability ML pipeline (~200GB) with rigorous regulatory/audit validation and quarterly executive reporting. Also built web-scraped product datasets with anti-bot protections at a startup and helped modernize an authn/authz service using AWS, plus led early-stage migration work from an internal warehouse to GCP with CI/CD and cloud observability.”
Jiacheng Yin
Intern software engineer specializing in AI, backend systems, and cloud infrastructure
“Backend/AI systems engineer who has shipped production LLM agents focused on prompt engineering, code generation, and incident-response automation. Stands out for combining strong agent orchestration and reliability engineering with measurable business impact, including 60-70% cost reductions, 45% lower monthly LLM spend, and a 5x increase in developer iteration speed.”
Kapil Sharma
Executive engineering leader specializing in AI platforms, LLMs, and healthcare SaaS
“Senior engineering leader in healthcare AI who combines org scaling with deep hands-on architecture work. At DriveHealth.ai, they helped evolve isolated workflows into a production-grade intelligent platform, standardizing a shared RAG+DCE architecture while leading teams of 50+ across engineering, AI, platform, QA, and DevOps.”