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Vetted TensorFlow Professionals
Pre-screened and vetted.
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and GPU-accelerated cloud systems
Intern Biomedical Data Scientist specializing in healthcare AI and LLM-based clinical NLP
Mid-level Generative AI & Machine Learning Engineer specializing in LLMs and RAG
Mid-level Data Engineer specializing in cloud-native big data pipelines and analytics
Mid-level Computer Vision Engineer specializing in robotics perception and mapping
Junior Robotics Engineer specializing in autonomous systems and robot learning
Senior Data Engineer specializing in cloud data platforms and real-time analytics
Senior Backend Software Engineer specializing in AWS serverless and data pipelines
Senior Software Engineer specializing in AWS distributed systems and developer tools
Mid-level AI/ML Engineer specializing in LLMs, ranking systems, and MLOps
Mid-level AI Solutions Architect & Product Leader specializing in enterprise GenAI systems
Principal Data Scientist / AI Engineer specializing in healthcare-native AI platforms
Senior FX Technical Director / Pipeline TD specializing in Houdini, Unreal, and real-time VFX
Rhutwij Tulankar
Engineering Manager and ML/Data Architect specializing in scalable data platforms and personalization
“Hands-on engineering manager at a marketing company leading a highly senior, distributed team (10 direct reports) while personally coding ~60–70% and owning end-to-end architecture across three interconnected products. Built agentic CRM automation and a reinforcement-learning-driven distribution layer for channel spend/bidding, with a strong focus on scalable design and observability (Prometheus/APM/logging) enabling frequent releases and few production incidents.”
Vigynesh Bhatt
Mid-level Software Engineer specializing in backend, cloud, and ML systems
“Software engineer with experience across Goldman Sachs, BYU Broadcasting, Juniper Networks, and an edtech startup (Doubtnut), spanning data migrations, AWS-based media backends, and microservices observability. Built a Redis/ElastiCache caching layer in front of DynamoDB/S3 to improve media delivery latency and cost, and created an SEO indexing automation tool using the Google Search Console API that saved ~15–30 person-hours per day.”
Ashish Ernest Jeldi
Senior Data Scientist specializing in LLMs, agentic AI, and MLOps
“Built and shipped a production agentic LLM tool that helps internal teams update technical product whitepapers using plain-language edit requests, with strong guardrails (citations, verification, refusal/clarify flows) to reduce hallucinations and maintain compliance. Experienced taking LLM workflows from rapid LangChain prototypes to more predictable, debuggable LangGraph agent graphs, and orchestrating end-to-end ingestion/embedding/indexing/eval/deploy pipelines with Kubeflow.”