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Vetted R Professionals
Pre-screened and vetted.
Swati Swati
Senior Data Scientist/Software Engineer specializing in ML systems and cloud DevOps
“AI software engineer with experience spanning LLM/RAG production systems and regulated fintech infrastructure. Built an end-to-end natural-language-to-SQL analytics assistant (Weaviate + GPT-4 + Supabase) shipped as an API with 92% accuracy and major time savings for non-technical users, and also owned demand-forecasting and CI/CD/containerization improvements for a Bank of America core banking deployment at Infosys.”
Atharva Deshmukh
Mid-level AI/ML Engineer specializing in GenAI and cloud MLOps
“Applied LLMs to high-stakes domains (wildfire risk for emergency teams and loan approval via a fine-tuned IBM Granite model), with a strong focus on reliability—using RAG-based cross-validation to reduce hallucinations and continuous ingestion pipelines (MODIS satellite imagery via AWS Lambda) to keep data current. Experienced in production orchestration and MLOps-style workflows using Airflow, AWS Step Functions, and SageMaker Pipelines, and collaborates closely with analysts on KPI-driven evaluation.”
PremKumar Gandla
Mid-level AI/ML Engineer specializing in MLOps, NLP, and scalable model deployment
“Built and deployed a production autonomous AI data analyst agent (LangChain + GPT + Streamlit on AWS) that turns natural-language questions into validated SQL, visualizations, and insights, cutting manual analysis time by ~50%. Emphasizes reliability and MLOps: schema-aware validation/guardrails to prevent hallucinations, scalable large-data processing, and Azure DevOps CI/CD + MLflow for automated deployment and experiment tracking.”
Gabriel Fagundes
Mid-level AI/ML & Backend Engineer specializing in AI platforms and computer vision
“Backend engineer with hands-on experience building real-time, low-latency systems: owned the Python backend for a real-time crowd-monitoring product (top 5% at HackHarvard 2025) using OpenCV, GPU YOLO inference (PyTorch), WebRTC, and OAuth. Also has production Kubernetes/GitOps experience (Helm/Kustomize, GitHub Actions, Argo CD), Kafka-based event pipelines, and executed a minimal-downtime on-prem PostgreSQL migration to AWS EC2.”
Manvi Panjwani
Mid-level Machine Learning Engineer specializing in cloud, governance automation, and distributed systems
“Governance engineer intern at GSK who built policy-as-code automation using Open Policy Agent/Rego integrated into GitHub CI/CD and Terraform workflows. Also built and shipped a voice-enabled expense tracking app using speech-to-text + LLM structured extraction with strong validation, retries, and semantic guardrails, and designed the supporting PostgreSQL data model with performance-focused indexing.”
Alicia Geng
Entry-level AI/ML Engineer specializing in AWS MLOps and computer vision
“Built and shipped a production RAG question-answering system using LangChain/OpenAI, Docker, and FastAPI, then reduced hallucinations through disciplined retrieval tuning and constrained prompting. Also implemented a custom evaluation framework (QA-pair dataset) to measure faithfulness/relevance and deployed containerized ML microservices on AWS ECS/Fargate with ALB and rolling, zero-downtime updates.”
Sai Krishna Mallikanti
Mid-level AI & Data Scientist specializing in LLMs, RAG, and healthcare NLP
“Built a production LLM/RAG solution for healthcare operations teams to query large policy and care-guideline repositories in natural language. Improved domain alignment using vector retrieval plus parameter-efficient fine-tuning and prompt optimization, validated through internal user testing and metrics, cutting manual lookup time by ~40%. Also has hands-on experience orchestrating automated ML pipelines with Apache Airflow.”
Soham Ravindra Lokhande
Junior Software Engineer specializing in agentic automation and AI platforms
“Backend-leaning founding/early engineer who built automation platforms end-to-end: FastAPI/Python services integrated with a Next.js/TypeScript frontend, including a production VNC streaming URL endpoint for cloud-instance desktop viewing. Also designed core Postgres user/workflow data models and built an agentic orchestration system with LangChain/LangGraph (sub-agents, validators, pause/resume), plus made scalability tradeoffs like S3 pre-signed uploads to keep microservices responsive.”
Riddhiman Deka
Mid-level Business Analyst specializing in analytics, operations, and supply chain
“Analytics candidate with hands-on experience improving enterprise reporting and operational decision-making at Reliance and Wendy’s. They combine SQL optimization, Python automation, sentiment analysis, and dashboarding to deliver measurable impact, including cutting report runtimes from 3 minutes to 1 minute, improving model accuracy from 70% to 80%, and reducing supplier past dues by 30%.”
Dinesh Guguloth
Mid-level Software Engineer specializing in full-stack cloud-native applications
“Full-stack engineer with cloud and GenAI experience who has owned production features end-to-end, including a reporting dashboard optimized from 14s to 5s using query/API refactoring and monitored via AWS CloudWatch. Also productionized an OpenAI-powered chatbot using LangChain with prompt design, guardrails, and evaluation via production logs and user feedback, and has led incremental legacy-to-microservices modernization with parallel run to avoid regressions.”
Priyanshi Gupta
Mid-level CRM Marketing Manager specializing in customer analytics and lifecycle marketing
“CRM and lifecycle marketer with hands-on experience across eCommerce retention, replenishment, post-purchase, and win-back programs. Brings a strong analytics lens to campaign strategy, using segmentation, holdouts, and A/B testing to optimize repeat purchase and revenue, with direct platform experience in Listrak, Braze, HubSpot, Shopify, and Nectar.”
Sudeepti Chalamalasetti
Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps
“Built a production RAG-based healthcare chatbot to retrieve patient medical documents spread across multiple platforms, reducing manual and error-prone searching. Implemented semantic search with custom embeddings (Hugging Face) and Pinecone, deployed via FastAPI/Docker on AWS SageMaker with MLflow tracking, and optimized fine-tuning cost using LoRA while orchestrating retraining pipelines in Airflow.”
Pranav Marla
Mid-level AI/ML & Full-Stack Engineer specializing in LLM agents and generative AI
“LLM/agent builder who shipped a live consumer AI-agent app (kalpa.chat) that visualizes complex reasoning as interactive graphs and abstracts multi-provider model usage via a unified wallet. Professionally has applied LangChain/LangGraph to IVR parsing and to scaling a football video-generation pipeline at DAZN, including shipping a VAR-specific retrieval/order fix via SQL after iterating with a non-technical PM.”
Ryan Grijalva
Mid-level Lifecycle & Email Marketing Manager specializing in automation and multi-channel campaigns
“Lifecycle/CRM marketer who built financing-journey email campaigns at Blue X Trade using Mailchimp and n8n, including an AI agent to validate user info and trigger instant correction emails—improving retention and ROI. Runs structured A/B tests on dynamic personalization (name/location/trading country) that increased engagement and bookings, and has led cross-functional promotions while managing third-party rewards integration issues with monday.com.”
Vaishnavi K
Mid-level AI/ML Engineer specializing in GenAI, MLOps, and anomaly detection
“LLM/MLOps engineer who has shipped a production RAG-based technical documentation assistant (FastAPI) cutting manual review by 45%, with deep hands-on retrieval optimization in Pinecone/LangChain (HNSW, hybrid + multi-query search, caching). Also brings healthcare domain experience—building Airflow-orchestrated EHR pipelines and delivering FDA-auditability-friendly predictive maintenance solutions using SHAP/LIME explainability surfaced in Power BI.”
“Backend/data engineer who builds Python (FastAPI) data-processing API services for internal analytics/reporting, emphasizing modular architecture, async performance tuning, and reliability patterns (health checks, retries, observability). Also migrated legacy on-prem ETL pipelines to Azure using ADF/Data Lake/Functions and implemented a near-real-time ingestion flow with Event Hubs plus watermarking to handle late events and deduplication.”
Aman Jain
Mid-level Software Engineer specializing in cloud-native data pipelines and ML platforms
“Backend engineer who has owned end-to-end delivery of Python/FastAPI microservices for real-time data processing and alerting, including performance tuning (Postgres optimization, caching, async processing). Strong DevOps/GitOps background: Docker + Kubernetes deployments with GitHub Actions CI/CD and ArgoCD-driven GitOps, plus experience supporting phased on-prem to AWS migrations and building Kafka-based streaming pipelines.”
Yash Pankhania
Mid-level AI Engineer specializing in LLMs, RAG, and data engineering
“AI Engineer Co-Op at Northeastern University who built a production Patient Persona Chat Bot to help nursing students practice clinical interactions, fine-tuning Llama 3 and integrating a LangChain + Pinecone RAG pipeline deployed on Amazon Bedrock. Emphasizes clinical accuracy and reliability with guardrails, retrieval filtering, and continuous evaluation, and also brings strong data engineering/orchestration experience (Airflow, EMR/PySpark, ADF, dbt, Databricks, Snowflake).”
nitesh bommisetty
Mid-level Data Scientist specializing in ML, NLP, and LLM-powered solutions
“AI/NLP-focused practitioner who built a zero-/few-shot LLM event extraction system on the long-tail Maven dataset, combining prompt-structured outputs with LoRA/QLoRA fine-tuning and rigorous F1 evaluation. Also implemented entity resolution/data cleaning pipelines and embedding-based semantic search using Sentence-BERT + FAISS, and has healthcare experience delivering a multilingual speech/translation mobile prototype using HIPAA-compliant Azure Cognitive Services.”
Santhoshi Priya Sunchu
Mid-level Data Scientist specializing in NLP and predictive modeling
“AI/ML practitioner in healthcare/insurance (Blue Cross Blue Shield) who built and deployed a production NLP system to classify patient risk from unstructured clinical notes. Experienced in end-to-end pipeline orchestration (Airflow, AWS Step Functions/Lambda/SageMaker) and real-time optimization (BERT to DistilBERT on AWS GPUs), with strong clinician collaboration to drive adoption.”
Farida Poor
Junior Machine Learning Engineer specializing in NLP and multimodal transformers
“Built and deployed LLM-powered agentic chatbot and text-to-SQL systems using LangGraph/LangChain (and Bedrock), structuring workflows as DAGs with planning/replanning and validation to improve tool-calling reliability and reduce hallucinations. Operates production feedback loops with online/offline metrics, drift detection, and LangSmith-based evaluation pipelines, and regularly partners with business stakeholders and clinicians using slide decks and visual charts.”
Snehitha Penumaka
Mid-level AI/ML Engineer specializing in predictive modeling and cloud ML pipelines
“LLM engineer/data engineer who has deployed production RAG systems for internal-document Q&A, building end-to-end ingestion, embedding, vector search, and FastAPI serving while actively reducing hallucinations and latency through rigorous retrieval tuning and caching. Also experienced in orchestrating cloud data pipelines (Airflow, AWS Glue, Azure Data Factory) and partnering with non-technical business teams to deliver AI solutions like automated document review.”
Abhiroopsudansh Karengula
Mid-level AI/ML Engineer specializing in production ML, RAG systems, and MLOps
“Built and shipped a widely adopted, production-grade RAG internal search assistant that unified scattered engineering knowledge, deployed as a FastAPI service on Kubernetes with FAISS + LangChain. Demonstrates deep practical expertise in retrieval tuning (chunking, hybrid search, re-ranking) and in making LLM workflows reliable in production via guardrails, monitoring, and evaluation, plus strong cross-functional delivery with non-technical operations teams.”
RIYA CHADDHA
Mid-level Data Engineer and Business Analyst specializing in cloud ETL and analytics
“Data analyst with cross-industry experience spanning insurance analytics at L&T Infotech and experimental imaging analytics at Mylyser. Stands out for building scalable SQL/PySpark data pipelines, standardizing business-critical metrics like claims lifecycle and policy retention, and delivering measurable impact such as 50%+ faster query performance and a 15% reduction in claims settlement time.”