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Vetted Machine Learning Engineers
Pre-screened and vetted.
Rohanth Gundu
Senior AI/ML Engineer specializing in LLMs, RAG, and MLOps
Nandivardhan Reddy
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Vishwam Shukla
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and scalable inference
Vibha Kumar
Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable MLOps
Jiwon Lee
Staff Software Engineer specializing in applied AI agents and full-stack product development
Zubair M
Mid-level AI/ML Engineer specializing in generative AI, LLMs, and MLOps
Sai Sathvik Yadlapalli
Mid-level Applied AI Engineer specializing in LLMs, MLOps, and real-time AI systems
Shashanka Oruganti
Mid-level AI/ML Engineer specializing in LLMs, multilingual NLP, and low-latency MLOps
Nitesh Vemanapalli
Senior AI/ML Engineer specializing in LLM agents, RAG, and production ML systems
Bhavani Patel
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Deepti Ahlawat
Mid-level Machine Learning Engineer specializing in Generative AI and LLM applications
Sai Chandra Bandi
Mid-level AI/ML Engineer specializing in Generative AI, LLM alignment, and RAG
“Built and productionized a real-time enterprise RAG pipeline to improve factual accuracy and reduce LLM hallucinations by grounding responses in constantly changing internal knowledge bases (policies, manuals, FAQs). Experienced in orchestrating end-to-end ML workflows (Airflow/Kubernetes), handling messy multi-format data with schema enforcement (Pydantic/Hydra), and maintaining freshness via streaming incremental embeddings plus batch refresh. Also delivers applied ML solutions with non-technical teams (marketing/CRM) for segmentation and personalized engagement.”
Subhash Mothukuru
Mid-level Machine Learning Engineer specializing in LLMs, generative AI, and MLOps
“Built and shipped a production LLM-powered medical scribe that generates structured clinical visit summaries using RAG, strict JSON schemas, and post-generation validation to reduce hallucinations. Experienced in making LLM workflows deterministic and observable (structured logging/metrics/tracing) and in evaluation-driven iteration with metrics like schema pass rate and edit rate; collaborated closely with clinicians and policy stakeholders at Scale AI to drive adoption.”
Sahil Bansal
Mid-level Backend & ML Engineer specializing in LLM systems and scalable AI pipelines
“Built and shipped a real-time AI phone agent for small businesses that handles bookings/FAQs/messages using streaming ASR, an LLM with tool-calling, and TTS; deployed to production for multiple paying customers. Demonstrates strong applied LLM reliability practices (tool-first grounding, retrieval, hard-negative testing, and production monitoring) and experience orchestrating multi-step AI workflows with Airflow, Prefect, and AWS Step Functions.”
Mohitha Chelikam
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and MLOps
Mohammed Raza Syed
Junior Machine Learning Engineer specializing in LLMs, data pipelines, and MLOps
Jayanth Tummalapenta
Mid-level Machine Learning Engineer specializing in search ranking and NLP
Chaitanya Battula
Mid-level AI/ML Engineer specializing in GPU-accelerated LLMs, RAG, and production MLOps
Kundan Sannapaneni
Mid-level Machine Learning Engineer specializing in MLOps and cloud-native ML systems
Vinya Kumar
Mid-level AI/ML Engineer specializing in LLMs, RAG pipelines, and multi-agent systems