Vetted scikit-learn Professionals

Aditya Jaiswal

Screened

Intern Software Engineer specializing in cloud, DevOps, and applied AI

Carlsbad, CA1y exp

“Full-stack engineer with startup ownership experience (Aiir) building 15+ TypeScript/Go microservice APIs on GCP Cloud Run with Kafka-based async event streaming and React CRM integrations for billing/analytics. Strong post-launch operator who tuned Oracle performance (partitioning/indexing/query optimization) and validated a 23% retrieval-time reduction via AWR, and has a quality/DevSecOps mindset (94% Pytest coverage, GitHub Actions, SonarQube, Twistlock, CloudWatch) including migrating 18+ production CI/CD pipelines.”

Utkarsh Mittal

Screened

Intern Data Scientist specializing in computer vision and LLM agents

Sunnyvale, CA0y exp

“Software engineering candidate with hands-on experience building and shipping LLM agents: created a production AI enrichment/coding agent at Covalent Metrology using Apollo.io + OpenAI, and built a Mistral hackathon router that dynamically selects among models to reduce token cost while maintaining quality. Also developed a real-time financial margin analysis agent that emails actionable insights and iterated on reliability issues (e.g., fixing misrouted emails, improving news relevance filtering).”

Bhavyasree Chinthala

Screened

Mid-level Data Engineer specializing in cloud data pipelines and real-time streaming

USA, USA5y exp

“Data engineer with PNC Bank experience owning high-volume financial transaction pipelines end-to-end (Kafka/REST ingestion through Spark/Glue transformations to Redshift serving) for risk and fraud analytics. Built strong reliability and data quality practices (Great Expectations, reconciliation, Airflow alerting, idempotent retries, incremental/windowed processing), reporting 40% ingestion efficiency gains and ~99.9% data accuracy.”

Junhui Huang

Screened

Intern Machine Learning Engineer specializing in LLMs, MLOps, and NLP

Providence, RI1y exp

“Built and deployed a production LLM-driven Dungeons & Dragons game where the model acts as a dungeon master, adding a structured combat system and a macro-state tree to ensure campaigns converge to a clear ending. Fine-tuned Gemini 2.5 Flash on Vertex AI and deployed on GCP with Kubernetes, using RAG over DnD rules/spells plus multi-agent orchestration (intent-based routing between narrative and combat agents) to reduce hallucinations and improve reliability.”

Vaibhav Sharma

Screened

Mid-level Software Engineer specializing in AI/ML and data platforms

Remote, USA5y exp

“AI/ML engineer who built a production agentic system to automate computational research experiments (simulation execution, parameter exploration, and numerical analysis) and mitigated context-window failures using constrained tool-calling/prompt-chaining patterns in LangChain with OpenAI tool-enabled models. Also has adtech/big-data pipeline experience at InMobi, orchestrating Spark jobs in Airflow to filter bot-like user IDs and publish clean IDs to an online NoSQL store for live serving, plus Apache open-source collaboration experience.”

Saksham Khatwani

Screened

Mid-level Software Engineer specializing in NLP and search systems

Aurora, United States3y exp

“Built an AI journaling app at HackCU 2025 featuring a speaking AI avatar with long-term memory via RAG (ChromaDB) and low-latency microservices coordinated through Kafka, including deployment under AMD/non-CUDA constraints using a quantized Llama 8B model. Also has Goldman Sachs experience deploying a Trade UI on Kubernetes with CI/CD rollback automation, plus a healthcare AI internship at CU Anschutz collaborating closely with physicians on diagnostic reasoning and dataset annotation.”

Suloni Praveen

Screened

Entry-Level Software Engineer specializing in data engineering and ML systems

Los Angeles, CA0y exp

“Built an end-to-end Next.js/TypeScript LLM-based scientific PDF analyzer using local Ollama/Llama inference to prioritize privacy and cost, producing structured research artifacts (e.g., authors/methods/findings) with ~92% extraction accuracy. At Qualtrics, helped replace a batch pipeline with a real-time, low-latency ML inference service (Python/Go on Kubernetes) using Redis caching, Grafana-based observability, and graceful fallbacks to protect UX during failures.”

“Analytics candidate with hands-on experience in both fraud and churn use cases, including SQL-based preparation of 6.5M transaction records and reproducible Python modeling workflows. Stands out for combining technical rigor in data quality, feature engineering, and imbalance handling with strong stakeholder alignment, metric definition, and dashboard adoption.”

“Analytics-focused candidate with hands-on experience using SQL and Python to clean messy business data, automate reporting, and build practical customer analytics solutions. Notable examples include a 70% reduction in reporting time through Python-based Excel automation at Shell and stakeholder-friendly retention/RFM segmentation work for small business clients in freight and winery contexts.”

Atharva Bhide

Screened

Entry Software Engineer specializing in AI/ML and multimodal systems

Los Angeles, CA1y exp

“Built and shipped a production healthcare AI platform for a clinic in Brea, LA that combined LLM-based clinical report generation, voice agents for appointment workflows, and camera-based patient monitoring. Stands out for pairing multimodal AI architecture with production-grade reliability and compliance practices, while delivering concrete business results including 90% workflow automation, 200 hours saved per month, and a 60% improvement in customer retention.”

“Analytics candidate with hands-on experience at BCBS building HIPAA-compliant SQL/Snowflake/Tableau pipelines across fragmented legacy healthcare systems. Stands out for turning a 5-day claims reporting process into a near real-time 10-minute dashboard and for pairing strong data engineering discipline with reproducible Python-based churn modeling that drove measurable retention outcomes.”

“Analytics-focused candidate with strong SQL, Excel, Python, and Tableau skills who supports payroll-, compensation-, and finance-adjacent processes through rigorous data validation and reconciliation. Stands out for uncovering a duplicate-record mapping issue that exposed roughly $250K in revenue leakage and for building repeatable controls, dashboards, and automated checks to improve reporting accuracy.”

“Early-career builder with hands-on project experience spanning Python data processing, a Chrome extension for autofilling job applications, and a sign-language glove system integrating sensors, microcontrollers, and a web interface. Stands out for approaching student and project work with a production-minded focus on validation, modularity, edge cases, and reliability.”

“Early-career analytics candidate with hands-on experience in SQL/Python data pipelines, Tableau reporting, and marketing engagement analytics across internship and startup settings. Stands out for combining rigorous data quality practices with practical AI system design, including an end-to-end GPT-4 grading capstone that emphasized explainability and human oversight.”

“Data-engineering-oriented candidate with hands-on experience building an agentic AI product and operational automation workflows. They described automating inventory-to-ERP discrepancy reconciliation with anomaly detection and daily reporting, and also have practical scraping/automation experience dealing with Cloudflare-protected sites using Selenium and Puppeteer.”

Amit Dharam

Screened

Junior AI/ML Software Engineer specializing in backend systems and cloud deployment

Tempe, AZ3y exp

“Built multiple end-to-end automation and data systems, including an Accio RAG pipeline combining PDF parsing, FastAPI, Neo4j, and vector search, plus Selenium-based scraping for a virtual try-on product. Stands out for reliability-minded engineering: automated testing, structured logging, validation layers, and a data-driven approach to debugging flaky automation that improved CI pass rates to over 98%.”

“AI/backend engineer who has owned production applied-ML systems end to end, including a Jitsi meeting intelligence platform with custom RoBERTa boundary detection, LLM summarization, and automated retraining from user feedback. Also has healthcare AI experience building a diabetes medication titration system with strict validation, drift monitoring, and safety guardrails—showing both product speed and high-stakes engineering rigor.”

“AI/LLM engineer with strong healthcare domain depth who has shipped production-grade agents for care coordination and clinical workflow automation. Stands out for combining Knowledge Graph RAG, LangGraph orchestration, and rigorous eval/guardrail systems to improve reliability in high-stakes environments, with measurable gains in review time, hallucination reduction, latency, and clinician adoption.”

“Product-minded full-stack engineer with experience shipping engagement features and core communication systems at DribbleUp and Expys. Stands out for combining rapid MVP execution with rigorous iteration: delivered a leaderboard feature that lifted engagement by 8% initially and 20% overall, built a chat MVP in 3 days, and has hands-on experience deploying LangChain-based concierge agents with evals and human review.”

“Full-stack engineer with enterprise banking experience at Citi and hands-on production AI agent work, including a multi-agent incident analysis pipeline using LangGraph, RAG, and LangSmith. Also built a zero-to-one healthcare operations dashboard spanning hospital workflows and AI-assisted clinical features, suggesting a blend of strong systems engineering and product-minded execution.”

“Platform-focused engineer/technical program leader working in silicon/wafer validation environments, with hands-on experience securing access to sensitive test results and engineering tooling. Has implemented RBAC/least-privilege controls with Azure Entra ID, Key Vault, PAM and integrated Checkmarx into dev workflows, while also deploying ML services on AKS using Bicep/Helm/Docker and Azure DevOps CI/CD with strong monitoring and incident response practices.”

“Robotics software engineer with UC Irvine capstone experience building an autonomous rover end-to-end: ROS 2 navigation (slam_toolbox + Nav2) on Jetson Xavier, depth point-cloud integration for obstacle avoidance, and an on-device speech-to-action interface that converts natural language into Nav2 goals. Also has prior full-time experience integrating a safety assurance decision engine into distributed autonomous drones over secured mesh networks, emphasizing reliable communication under real-world network constraints.”

“Robotics software engineer who owned the end-to-end navigation stack for a mobile manipulation robot (Cone-E), integrating ZED-2i SLAM into a real-time occupancy grid with live obstacle avoidance, A* planning, and lookahead control. Strong in real-time debugging and stability improvements (goal snapping/locking, obstacle persistence, rate-limited replanning) and validates changes on hardware, supported by simulation (Gazebo/Webots) and Docker/CI-based testing.”

“LLM/RAG practitioner who productionized an LLM-driven customer communication and transaction understanding system at PayPal, emphasizing privacy/compliance guardrails and large-scale data normalization. Experienced in real-time debugging of hallucinations via retrieval pipeline tuning and in leading hands-on developer workshops and sales-aligned POCs to drive adoption.”