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Vetted Python Professionals

Pre-screened and vetted.

YR

Mid-level AI/ML Developer specializing in FinTech fraud detection and GenAI assistants

MO, USA4y exp
Edward JonesUniversity of Central Missouri
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RR

Mid-level Data Scientist specializing in financial ML, NLP, and MLOps

San Diego, CA5y exp
Morgan StanleySan Diego State University
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JF

Mid-level AI/ML Software Engineer specializing in Generative AI and NLP

Remote5y exp
EmerjenceBoston University
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AO

Anthony Odinukwe

Screened ReferencesStrong rec.

Senior Full-Stack Engineer specializing in React/Next.js web applications

Calgary, Canada6y exp
WestJetBow Valley College

Frontend-focused engineer who has led end-to-end delivery for an ecommerce web app and built complex React + TypeScript dashboards with real-time data and multi-step workflows. Strong in scalable architecture (typed API layers, shared hooks, design systems), quality at scale (Jest/RTL + Playwright), and performance optimization (virtualization, lazy-loading, memoization). Experienced shipping high-impact checkout changes via feature-flagged rollouts with metric/error monitoring and rapid iteration.

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SD

Srijan Dokania

Screened ReferencesModerate rec.

Junior Robotics & Machine Learning Engineer specializing in perception, SLAM, and edge AI

Boston, MA2y exp
Field Robotics Lab (Northeastern University)Northeastern University

Built and deployed an Azure-based, fine-tuned CLIP visual retrieval system at Staples for a ~300k-item product catalog, improving edge-case recall by 12% by engineering a custom delta-similarity/dynamic-margin loss. Also has robotics experience using ROS2 for sensor/compute orchestration, including GPS-time-synchronized sensor triggering for robot swarms and latency-bounded optical-flow benchmarking for edge deployment.

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DJ

Devon Johnson

Screened ReferencesStrong rec.

Executive Cybersecurity & Infrastructure Architect specializing in incident response and resilience

Nashville, TN19y exp
Ceyepher SecurityAustin Peay State University

Founder of pre-revenue cybersecurity startup Ceyepher Security; has already set up lead-intent sourcing, automated pipeline/CRM analytics, and outbound marketing. Plans to raise capital after landing first clients to demonstrate value via revenue, whitepapers, and customer testimonials; interested in studio support to accelerate sales. Mentions a disability that has enabled significant time honing computer science skills and is open to joining innovative work even outside their own company.

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SA

Sharath Addepalli

Screened ReferencesStrong rec.

Mid-Level Software Engineer specializing in Python microservices and scalable web APIs

Franklin, TN3y exp
NissanUniversity of Florida

Backend engineer who replaced an Excel-heavy forecasting workflow with a secure, auditable FastAPI system (React UI + relational model + async workers), emphasizing deterministic processing, idempotency, and versioned ledger-style ingestion. Led a monolith-to-FastAPI migration at Bounteous using a strangler approach, feature-flagged incremental rollout, and data reconciliation/shadow-compare to protect integrity while scaling onboarding workflows.

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NK

Naga Karumuri

Screened ReferencesStrong rec.

Mid-Level Full-Stack Engineer specializing in AI and 3D computer vision

Newark, NJ4y exp
DiffStudioNJIT

Built and productionized an LLM-driven document verification workflow for a construction firm’s submittals process, moving from a Vercel/Next.js prototype to a FastAPI + LangChain/LangGraph backend with background workers and multi-server deployment. Uses LLM tools (e.g., OpenAI Codex/Cloud Code) for rapid development and log-driven root cause analysis, and partners with customer teams on evaluation metrics and iterative improvements.

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AP

Ashwith Poojary

Screened ReferencesStrong rec.

Mid-level Software & AI Engineer specializing in Robotics, LLMs, and Reinforcement Learning

4y exp
Arizona State UniversityArizona State University

Robotics/AI Master's thesis researcher building an LLM-driven workflow to generate and evaluate robot policies before running them in an environment. Also built a local LLM-based real-time target-tracking robot using a pan-tilt camera with LangChain + Ollama, and has hands-on ROS 2/Gazebo experience including URDF-based simulation and a TurtleBot multi-agent chase project.

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JB

Jayeetra Bhattacharjee

Screened ReferencesStrong rec.

Mid-level AI/ML Engineer specializing in LLMs, NLP, and analytics automation

Bristol, UK4y exp
TCSUniversity of Bristol

AI/ML Engineer (TCS) who built and deployed a production LLM-powered audit transaction validation service to reduce manual review of unstructured transaction records and comments. Implemented a LangChain/Python pipeline for extraction/normalization and discrepancy detection, with strong production reliability practices (decision logging, dashboards, labeled eval sets) and a human-in-the-loop auditor feedback loop to improve precision/recall under strict data-sensitivity and near-real-time constraints.

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RG

Rithindatta Gundu

Screened ReferencesStrong rec.

Mid-level AI/ML Engineer specializing in LLM systems and cloud MLOps

San Francisco, CA4y exp
Wells FargoSeattle University

Built a production LLM-powered fraud detection platform at Wells Fargo, combining OpenAI/Hugging Face models with RAG-based explanations to make flagged transactions interpretable for risk and compliance teams. Delivered low-latency, real-time inference at high scale on AWS (SageMaker + EKS), with strong observability and security controls, reducing manual reviews and false positives in a regulated environment.

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LD

Lavrenti DeLavrenti

Screened ReferencesStrong rec.

Director-level Technology Leader specializing in cloud-native platforms, AI/ML, and SaaS

Remote15y exp
Alioni Tech LabsGeorgian Technical University

Engineering leader (Director/VP level) who has repeatedly aligned product and engineering through ROI-driven quarterly roadmaps and strong stakeholder communication, including board presentations. Built a parallel cloud team to migrate an on-prem product to the cloud, credited with delivering $9M ARR, and led a Python monolith-to-serverless event-driven microservices transformation. Currently manages distributed teams across Mexico, India, and the US using pod-based structures, clear KPIs, and a supportive accountability culture.

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SP

Suparshwa Patil

Screened ReferencesStrong rec.

Mid-level Software Engineer specializing in Agentic AI and RAG systems

Remote, California4y exp
One CommunityPurdue University

Built and shipped a production AI-powered Q&A/RAG onboarding assistant at One Community Global that unified knowledge across Notion, Google Docs, and Slack, cutting volunteer onboarding time by 45%. Demonstrates strong end-to-end ownership: LangChain agent orchestration integrated into a FastAPI backend, rigorous evaluation (200-query dataset, ~85% accuracy), and production feedback/monitoring with source-attributed answers to build user trust.

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VV

Vaishnavi Veerkumar

Screened ReferencesStrong rec.

Mid-level AI Engineer specializing in GenAI and RAG systems

Boston, MA4y exp
VizitNortheastern University

AI engineer who built a production e-commerce system that analyzes product images alongside sales and demographic data to generate actionable creative recommendations, now used by 20+ clients. Also built orchestrated document/agent pipelines (Airflow, LangGraph) including a compliance drift detector auditing 401 compliance documents, with an emphasis on traceability, logging, and production integration.

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LV

Mid-level Software Engineer specializing in SRE, observability, and LLM-powered automation

Richardson, TX2y exp
CiscoWestcliff University
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JL

Joseph Lin

Screened ReferencesModerate rec.

Intern Software Engineer specializing in full-stack development and applied AI

New York, NY0y exp
Real Value CapitalNYU

Internship experience building an end-to-end medical AI pipeline that extracts and normalizes messy medical PDFs, fine-tunes BioBERT to classify tumor-related statements (including negation/ambiguity handling), and integrates image-model outputs (MedSAM/GroundingDINO) for tumor localization and classification. Also worked on an LLM/RAG system to draft IPO prospectuses using retrieved regulatory/financial sources (including SEC EDGAR) with structured prompts to reduce hallucinations.

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AH

Anthony Hernandez

Screened ReferencesStrong rec.

Mid-level Game Designer specializing in systems, balance, and live updates

Los Angeles, CA6y exp
GrabUSC

Game designer currently leading design on a Mario Party-like party game, owning mode design, economy, and meta-progression. Uses playtests and A/B tests to tune fairness-focused systems (e.g., dynamic power-ups accounting for player standing and turn order) and prototypes quickly in UE5 Blueprints. Previously shipped a mixed-reality version of Knockout League’s Knockout Alley mode for a Quest 3-aligned release.

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NG

Naga Gayatri Bandaru

Screened ReferencesModerate rec.

Mid-level AI/ML Engineer specializing in MLOps and production ML systems

Cleveland, Ohio3y exp
Cleveland ClinicSan José State University

Backend/ML engineer who has shipped high-scale real-time systems across e-commerce and healthcare: built a PharmEasy real-time recommendation engine for ~2M monthly users (cut feature latency 5 min→30 sec; +15% cross-sell) and architected a HIPAA-compliant multimodal clinical diagnostic workflow (DICOM+EHR) with XAI, MLOps (MLflow/Airflow/K8s), and drift/monitoring guardrails supporting 10k+ daily predictions.

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MP

Manasa Pantra

Screened ReferencesStrong rec.

Junior Software Engineer specializing in AI, LLM systems, and full-stack development

Stony Brook, NY2y exp
Stony Brook UniversityStony Brook University

Product-focused full-stack engineer at startup (Zippy) who shipped a production multi-agent AI system for restaurant operations plus payments workflows. Built end-to-end: RAG grounded on a Notion knowledge base, structured function-calling task routing, FastAPI/JWT multi-tenant backend, and a polished React+TypeScript owner dashboard. Has real production incident experience (duplicate Stripe webhooks) and reports ~94% task-routing accuracy under load.

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AA

Abnik Ahilasamy

Screened ReferencesModerate rec.

Intern LLM/GenAI Engineer specializing in RAG, agentic systems, and low-latency inference

Chennai, India0y exp
Larsen & ToubroArizona State University

Interned at Larsen & Toubro where they built and deployed an agentic RAG document question-answering system to reduce time spent searching documents and improve trustworthiness. Implemented ReAct-style multi-step orchestration with LangChain/LlamaIndex plus evidence-bounded generation, grounding/citations, and rigorous evaluation—cutting latency ~40%, hallucinations ~35%, and unsafe outputs ~40% while collaborating closely with non-technical business/ops stakeholders.

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IP

Ivan Pavkovic

Screened

Senior Paid Ads Specialist specializing in multi-platform performance marketing

Remote9y exp
KPMGUniversity of Zagreb

Performance marketer focused on e-commerce growth, managing $120K/month in spend across Google and Meta with reported 5x+ ROAS. Emphasizes full-funnel structure and creative iteration (copy, hooks, UGC) in collaboration with in-house creative teams, and prioritizes client reporting around sales/profit outcomes.

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ST

Mid-level Robotics & ML Engineer specializing in perception, control, and scalable systems

Mumbai, India3y exp
TCSNortheastern University

Robotics software engineer/researcher focused on perception, SLAM, and sensor fusion, with hands-on experience taking systems from simulation to embedded/real-time deployment. Led transparent-surface (glass) detection using GDNet and achieved a major real-time speedup (~7–9 FPS to ~30 FPS) while preserving >90% recall, and has built ROS-based EKF GPS-IMU fusion plus profiled/optimized Visual SLAM for performance and memory stability. Also brings production-style deployment skills via Docker/Kubernetes orchestration of ML inference services with autoscaling and model update rollouts.

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ZL

Zongguang Liu

Screened

Entry Robotics Engineer specializing in ROS 2 autonomy and simulation (Isaac Sim)

Las Vegas, NV1y exp
RichTech RoboticsMichigan Technological University

Robotics software engineer (PhD background) who owned an end-to-end autonomy stack for a 2025 GTC demo, integrating ROS2/MoveIt2 with a high-fidelity NVIDIA Isaac Sim environment for regression testing and sim-to-real validation. Has hands-on experience optimizing MoveIt2 planning (parallel pipelines + evaluation metrics) and building outdoor Nav2 localization using dual EKF with GNSS and LiDAR/IMU sensor fusion; currently building simulation environments at Richtech Robotics.

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SS

Senior Product Marketing Leader specializing in GTM strategy and RevOps analytics

Dallas, TX7y exp
BYJU'SBoston University

Growth creative/performance marketer from BYJU'S (India) who runs disciplined creative experimentation across Meta, TikTok, and YouTube. Notably shifted messaging from feature-led to outcome/testimonial-led creative, delivering CPA down 27%, ROAS up 35%, and +11% trial-to-paid conversion, and has experience leading a small creative pod (editors + writer) with a rapid-iteration production system.

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