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Vetted PyTorch Professionals
Pre-screened and vetted.
Hitha Magadi Vijayanand
Mid-level Backend Software Engineer specializing in AWS cloud and FinTech platforms
“JP Morgan engineer and Texas A&M student web developer who has owned production systems end-to-end, including a real-time ML training workflow that improved internal search relevance by 30%. Experienced with AWS cloud migrations and operating containerized services on ECS with CloudWatch+ELK observability, Terraform infra, and Spinnaker CI/CD; also built event-driven pipelines with RabbitMQ and Elasticsearch at 1M+ record scale.”
Yupeng Tang
Junior Machine Learning Engineer specializing in LLM systems and GPU inference
“LLM/agent engineer who shipped a production RAG-based recommendation + explanation system that replaced a traditional recommender stack, delivering ~20% CTR lift (and +8% after a reliability iteration) with strong cold-start performance. Demonstrates strong production rigor: schema-constrained generation, typed tool calling, explicit state/orchestration, deep monitoring/feedback loops, and safe integration with messy ERP inventory/order data using normalization, idempotency, and conflict-resolution guardrails.”
Jathin Shettigar
Intern Software Engineer specializing in edge AI deployment and distributed systems
“Full-stack engineer who built an enterprise search platform (Codlens) delivering natural-language Q&A over Jira/Slack using embeddings, vector DB search, re-ranking (RRF), and LLM responses with source grounding. Also designed and benchmarked a distributed IAM system with Postgres transaction-log replication and Raft-based quorum consistency, reporting ~253 TPS at ~60ms latency in a multi-node setup. Experience spans early-stage startups (Zetic AI, Sagwara Capital) and large-scale orgs (Akamai, Atlassian).”
Anvith Reddy Dodda
Mid-level AI Engineer specializing in GenAI, NLP, and MLOps
“LLM/agentic-systems engineer with PayPal experience hardening an LLM-powered fraud support assistant from prototype to production, focusing on low-latency distributed architecture, rigorous evaluation/testing, and security/compliance. Comfortable in customer-facing and GTM contexts—runs technical demos/workshops, builds tailored pilots, and aligns sales/CS with engineering to close deals and drive adoption.”
Aashna Kunkolienker
Junior AI Engineer specializing in agentic workflows and ML platforms
“Building a production LLM/agent system for a leading US dental provider that extracts rules from payer handbooks/portals and EDI 271 responses to validate and improve patient cost estimates. Combines GCP stack (BigQuery, GKE, Cloud Run, Pub/Sub, Vertex AI) with strong agent reliability practices (observability, validator agents, grounding, PII/hallucination guardrails, confidence scoring) and has led non-technical customer stakeholders on enterprise ServiceNow↔Aha sync and AI-powered enterprise search/summarization.”
Jincheng Pang
Principal Data Scientist specializing in healthcare analytics and medical imaging AI
“Developed an LLM-driven recommendation agent in Azure Databricks to triage oncology patients and trigger second-opinion case creation using medical claims and EHR data. Uses ICD-10/CPT/J-code features in prompts, embeddings + vector DB similarity, and a backtesting framework emphasizing recall to avoid missing clinically relevant cases while supporting business revenue.”
Ali Rahmati
Senior Machine Learning Engineer specializing in optimization, LLMs, and on-device AI
“Engineer with hands-on experience debugging and hardening a fixed-point implementation for an internal PoC, quickly diagnosing overflow/underflow issues that caused intermittent failures across thousands of runs and delivering a code fix. Comfortable presenting technical solutions with layered slide depth and doing follow-up deep dives for interested stakeholders, though has limited direct customer/sales partnership experience.”
Chia-En Lu
Junior AI/ML Systems Engineer specializing in LLM infrastructure and distributed training
“Built and shipped a production NMT system translating medical documentation for a rare/low-resource language, tackling data scarcity with retrieval-driven pattern matching plus dictionary/grammar- and LLM-based augmentation and validating quality with a linguistic expert. Also develops agentic LLM workflows with LangChain/LangGraph (including a deep-research style system) and has experience aligning medical AI deployments with clinician-defined risk metrics and human-in-the-loop decision making.”
Seyi R. Afolayan
Mid-level Robotics & Controls Engineer specializing in safe autonomy and perception-aware motion planning
“Robotics software engineer who built an open-source, real-time Cartesian controller for Universal Robots UR5/UR5e, targeting sub-mm accuracy at 500 Hz within ROS2/ros2_control. Demonstrates strong real-time debugging skills (timing profiling, singularity handling with Tikhonov regularization) and sim-to-real iteration using Gazebo/Isaac Sim plus physical hardware tuning; also has ROS1 experience building URDF/xacro and EKF configs for an underwater vehicle and has developed drone/robot packages.”
Jainum Sanghavi
Mid-level DevOps Engineer specializing in cloud automation and Kubernetes platforms
“Robotics/ML engineer who has built SO(3)-equivariant models for robotic manipulation, including custom equivariant layers and differentiable point-cloud rasterization/derasterization workflows. Also brings 2 years of DevOps experience in banking systems, automating CI/CD and infrastructure at scale (managed 180 OCI servers; reduced rebuild downtime by 80%).”
Niteesh Ganipisetty
Mid-level AI/ML Engineer specializing in Generative AI, NLP, and Computer Vision
“Built an LLM-powered learning assistant (EduQuizPro/EduCrest Pro) that uses RAG over URLs and PDFs to generate quizzes, notes, and explanations for students/professors. Emphasizes production robustness—implemented dependency fallbacks (FAISS/Sentence Transformers/Gradio), CLI-safe mode, and NumPy-based indexing—along with a custom orchestration layer to keep multi-step AI workflows reliable.”
“Built and productionized an AI-native, agentic appeals decisioning system for health insurance operations, automating 500k+ scanned appeals/year. Delivered measurable impact by cutting review time from 12–15 minutes to ~3 minutes and auto-resolving ~85% of cases with strong auditability, evaluations, and human-in-the-loop guardrails, deployed as containerized microservices on Azure AKS.”
Adrian Melian
Staff Technical Artist specializing in character pipelines, rigging, and tools for games
“Lead Tech Artist/animation systems specialist with UE5 locomotion and VR experience, including a complex VR mech setup where player arm motion drove mech arms with intentional lag using IK and follow points. Has shipped experience across Meta Horizon VR (built Unity profiling tooling) and Call of Duty (animation performance fixes for runtime cinematics), plus a strong track record building artist-first pipelines like modular rig builders and an AI skinning framework.”
silin liu
Mid-level AI/ML Engineer specializing in LLM agents, RAG, and enterprise ML systems
“Built a production multi-agent recommendation/RAG system for internal data analysts to speed up weekly report creation by improving document discovery and automating report/SQL generation. Implemented LangGraph-based orchestration with deterministic agent routing, robust error handling (interrupt/resume), and metadata-driven semantic chunking for diverse PDF/document formats, plus monitoring for latency, throughput, and token/cost efficiency.”
Ibrahim Kurban Ozaslan
Junior Robotics & Controls Researcher specializing in optimization, MPC, and reinforcement learning
“Robotics software candidate who designed and implemented a hierarchical motion-planning and whole-body control pipeline for a 37-state Spot robot to traverse complex terrain, using Graph of Convex Sets for safe footstep selection plus optimization-based IK and nonlinear trajectory optimization for joint trajectories/contact forces. Strong in optimization-heavy robotics workflows (PyDrake, MATLAB/Simulink) and methodical debugging down to signal-level and numerical stability; has not used ROS/ROS2 yet.”
Shivam Udeshi
Intern Robotics/ADAS Engineer specializing in perception, sensor fusion, and state estimation
“Robotics software engineer who built a multi-agent dense warehouse mapping system in ROS 2, including LiDAR-camera fusion SLAM, timestamp-based synchronization, and DDS-based inter-robot pose/keyframe exchange under bandwidth constraints. Also applied Gaussian Splatting for selective photorealistic dense reconstruction and optimized real-time performance with node composition, bounded queues, and QoS tuning; experienced with Gazebo/CARLA/Unity simulation and Dockerized ROS 2 deployments.”
Shravya Shashidhar
Intern Software Engineer specializing in LLM agents and full-stack development
“Embedded C++ engineer with Bosch automotive infotainment experience, owning real-time audio middleware modules with strict latency/memory constraints. Strong in profiling/optimizing deterministic behavior, debugging hardware-specific intermittent issues, and building automated test + CI pipelines; currently ramping up on ROS2 concepts (DDS, nodes/topics/services) to transition toward robotics.”
Fatim Majumder
Junior ML research engineer specializing in evaluation platforms and applied machine learning
“ML/LLM infrastructure engineer who built and shipped a production internal evaluation + failure-analysis agent (Arthur AI / R3AI context) that orchestrated end-to-end benchmarks with deterministic lineage, regression detection, and root-cause reporting at 5,000+ benchmarks/week. Also built backend observability and data validation systems for analytics pipelines at FullStory processing ~3.4B weekly events, emphasizing schema validation, quarantine fallbacks, and idempotent operations.”
Abhishek Adinarayanappa
Junior Software Engineer specializing in backend, cloud, and machine learning systems
“Built Digipulse, a university project that ingested and clustered Bluesky tweet data at scale and used Gemini to generate near-real-time topic summaries, processing 1M+ tweets per day. Also brings Intel experience with Prometheus and Kubernetes, including production monitoring and incident troubleshooting.”
Zahra Shergadwala
Junior Machine Learning Engineer specializing in AI, computer vision, and data systems
“Built and owned an end-to-end AV operations automation and dashboarding platform for USC event operations, used daily to coordinate hundreds of live events. Delivered a React/TypeScript full-stack system integrating Smartsheet APIs with strong reliability practices (typed contracts, validation/fallbacks, safe rollouts) and experience with queue-based microservice patterns (idempotency, retries, DLQs, monitoring).”
Aarushi Mahajan
Mid-level AI/ML Engineer specializing in NLP, Generative AI, and MLOps
“Internship experience shipping production AI systems: built an end-to-end RAG platform (Python/FastAPI + LangChain/LangGraph + vector search) to answer support questions from unstructured internal docs, with a strong focus on hallucination prevention through confidence gating and rigorous offline/online evaluation. Also delivered an AI-driven personalization/analytics feature using an unsupervised clustering pipeline, iterating with PMs to align statistically strong clusters with actionable business segmentation.”
Ming Wang
Entry-level Software Engineer specializing in AI and FinTech
“Recent college graduate and software engineer who relies heavily on AI-assisted development, reporting that roughly 85% of code in a recent initiative was AI-generated and then manually reviewed. Has built customer-facing AI features including personalized recommendations and an internship chatbot tied to product advertising, with exposure to API communication, database checks, and conversation monitoring.”
Warren Thompson
Executive AI engineering leader specializing in SaaS, cloud platforms, and applied machine learning
“Senior engineering executive who has spent the last decade leading large-scale platform modernization while staying deeply hands-on in architecture, debugging, and code reviews. He has led 120+ person organizations, built cloud-native SaaS and identity platforms across regulated and enterprise domains, and ties engineering decisions directly to revenue outcomes, including contributing to Wind River's $1B+ milestone.”
Saurabh Kumar
Intern Full-Stack Developer specializing in MERN and AI applications
“Frontend-focused engineer with hands-on experience building sophisticated browser UIs, including a real-time WebRTC video chat platform for IIT Kanpur students and a high-performance NBA analytics dashboard. Stands out for deep browser performance knowledge, expert-user interface design, and competition-level execution that helped earn a global rank 2 finish.”