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Vetted BigQuery Professionals
Pre-screened and vetted.
Senior Full-Stack Engineer specializing in AI, cloud, and Web3 platforms
Mid-level MLOps/Machine Learning Engineer specializing in cloud-native production ML
Mid-level Machine Learning Engineer specializing in Generative AI and LLMOps
Mid-Level Full-Stack Software Engineer specializing in cloud integrations and real-time systems
Director-level Applied ML Engineer specializing in GenAI, LLM systems, and MLOps
Senior Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Software QA Engineer specializing in web and mobile testing
Mid-Level Full-Stack Software Engineer specializing in web apps and data pipelines
Senior Full-Stack & AI Engineer specializing in FinTech and Healthcare
Senior Data Engineer specializing in Machine Learning and Healthcare Data Platforms
Senior Full-Stack Developer specializing in MERN, cloud platforms, and LLM-powered applications
Mid-level Full-Stack Developer specializing in modern web apps and cloud platforms
Mid-level Data Analyst specializing in BI and healthcare insurance analytics
Mid-level Data Analyst specializing in analytics, AI, and business intelligence
Mid-level Generative AI Engineer specializing in LLMs, RAG, and NLP systems
Junior Full-Stack Software Engineer specializing in cloud, distributed systems, and AI
Akash Mishra
Mid-level Data Engineer specializing in ETL pipelines on GCP
“Full-stack engineer from Larix Technologies who led a Next.js migration feature: an internal real-time workflow status dashboard built with App Router/TypeScript using server components for initial render and client polling for live updates. Demonstrates strong post-launch ownership—monitoring latency/error rates, adding caching and payload reductions, and optimizing Postgres queries/indexes—plus experience building durable RabbitMQ-based message routing workflows with idempotency, retries, and dead-letter queues.”
Harikrishna Kadari
Mid-level Data Engineer specializing in cloud ETL and big data pipelines
“Data engineer focused on building reliable, production-grade pipelines and data services end-to-end, including a 50+ GB/day pipeline ingesting from APIs/files into Snowflake with PySpark/SQL transformations. Emphasizes strong data quality controls, monitoring/retries, and performance optimization, and has also shipped a Python data API with caching and backward-compatible versioning.”
Jeet Choksi
Mid-level Machine Learning Engineer specializing in real-time AI and data platforms
“ML/NLP engineer who has built production systems end-to-end: a real-time recommendation platform (100k+ profiles) using BERTopic-style clustering and a RAG-based news summarization/recommendation stack with ChromaDB. Strong focus on scaling and reliability (GPU batching, Redis caching, Kafka ingestion, Docker/Kubernetes, Prometheus/Grafana) and on maintaining model quality over time via drift monitoring and retraining triggers.”
Karthikeya Arra
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and MLOps
“Backend/ML engineering candidate focused on fintech automation who architected a zero-to-one agentic/LLM-enabled system to reconcile messy financial documents and bank transactions, reporting ~40% operational efficiency gains. Experienced migrating monoliths to event-driven microservices with incremental rollout via reverse proxy, and implementing production-grade security (OAuth2/JWT, RBAC, Supabase RLS) plus resilience patterns (timeouts/retries under concurrency).”