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Vetted Feature Engineering Professionals
Pre-screened and vetted.
Mid-level AI & Machine Learning Engineer specializing in production ML and LLM applications
Mid-level Machine Learning & Data Engineer specializing in MLOps and cloud data platforms
Mid-level AI/ML Engineer specializing in LLMs, agentic systems, and MLOps
Mid-level Software Engineer specializing in cloud infrastructure automation and ML systems
Senior Full-Stack Developer specializing in AI-driven cloud-native systems
Mid-level AI & Machine Learning Engineer specializing in computer vision and MLOps
Mid-level AI/ML Engineer specializing in production ML, NLP, and computer vision
Intern Machine Learning Engineer specializing in NLP and LLM/RAG systems
Mid-level AI/ML Engineer specializing in NLP, Computer Vision, and Generative AI
Principal AI Platform Architect specializing in agentic AI and enterprise LLM infrastructure
Mid-level AI/ML Engineer specializing in GenAI, MLOps, and big data on cloud platforms
Senior Data Engineer specializing in cloud lakehouse platforms and healthcare data
Mid-level AI Data Engineer specializing in real-time streaming and LLM-powered fraud analytics
Mid-level Data Engineer specializing in analytics engineering, ML forecasting, and modern data stacks
Mid-level Software Engineer specializing in backend systems, distributed systems, and applied AI
Rohith Sadanala
Mid-level Machine Learning Engineer specializing in Generative AI and MLOps
“LLM/agent engineer who has shipped production RAG chatbots in sustainability-focused domains, including a packaging recommendation assistant that standardized messy user inputs and used Pinecone-backed retrieval over product/regulatory data. Experienced orchestrating end-to-end ML workflows with Airflow and AWS Step Functions/Lambda, emphasizing reliability (property-based testing, circuit breakers, OpenTelemetry) and measurable performance (latency/cost). Partnered closely with non-technical leadership to ship 3 weeks early, driving adoption by 150+ businesses and ~20% reported waste reduction.”
Devisri Veeramachaneni
Senior Software Engineer specializing in cloud backend systems and LLM-powered agents
“Amazon Fire TV Devices engineer who built and shipped a production LLM-powered lab triage and validation system that grounds recommendations in internal runbooks/known-issue data and pushes evidence-based actions via dashboards and Slack. Emphasizes safety and measurability with structured JSON outputs, replay-based evaluation on historical incidents, and production metrics (e.g., disagreement rate and time-to-first-action), plus cost/latency optimizations like caching, batching, and rule-based fast paths.”
Nandini Kosgi
Mid-level AI/ML Engineer specializing in LLMs, RAG, and fraud/risk analytics in Financial Services
“Built and shipped a production-grade GenAI Fraud & Compliance Investigation Copilot for a large US bank, integrating OCR docs, structured data, and prior case history to generate grounded, regulator-friendly summaries and red-flag highlights. Demonstrates strong end-to-end LLM systems engineering (LangGraph/LangChain, hybrid retrieval with FAISS+BM25, guardrails/citations, streaming/latency optimization) plus rigorous evaluation and close partnership with compliance stakeholders.”
Sahithi S
Mid-level AI/ML Engineer specializing in NLP, MLOps, and Generative AI
“Built and deployed a production generative AI chatbot at NVIDIA using LangChain + GPT-3 integrated with internal data sources, cutting response time nearly in half and improving CSAT by ~12 points. Also delivered LLM-driven QA tools by fine-tuning Hugging Face transformer models and deploying via an AWS-based pipeline (Lambda/Glue/S3) with orchestration (Airflow/Step Functions), CI/CD, Kubernetes, and monitoring (MLflow/Splunk/Power BI).”