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Vetted Research Assistants
Pre-screened and vetted.
Mid-level Machine Learning Engineer specializing in reinforcement learning and multimodal AI
Intern Computer Vision/ML Engineer specializing in mapping, localization, and scalable inference
Senior Marketing Analytics & Digital Strategy Professional specializing in data-driven performance optimization
Mid-level Machine Learning Engineer specializing in Bayesian inference and reinforcement learning
Staff AI Systems Engineer specializing in multi-agent and distributed platforms
Danny Klein
Intern Robotics Engineer specializing in robotics testing, controls, and automation
“Robotics engineering intern and mechanical engineering master’s student who bridges hardware testing and ML/ROS2 software: built a PyTorch model to map motor test data across motor types using electrical specs (Kv/Kt/R/L) and validated it against new motors to meet strict torque/thermal accuracy targets. Also integrated CNN-based perception into ROS2 for real-time navigation and implemented MPC with time-synchronized multi-topic messaging to avoid stale-data control issues.”
Ritika Ghosh
Junior Robotics & AI Engineer specializing in ROS2 autonomy and real-time computer vision
“Robotics software engineer from Stanley Black & Decker’s autonomous team who built and deployed a ROS2-based model predictive control system for a commercial autonomous lawn mower, integrating real-time localization, Nav2 planning, and custom control under real-time constraints. Has hands-on field debugging experience (Foxglove, TF timing, covariance/noise tuning) to resolve issues that only appeared outside simulation, plus containerized deployment and CI/CD experience.”
Varmin Singh
Intern Software Engineer specializing in data engineering and LLM/RAG systems
“Built and productionized enterprise LLM/RAG systems, including a Boeing internal solution that gave 400+ program managers conversational access to 1M+ rows of schedule data, with strong emphasis on governance, reliability, and reducing hallucinations in tabular domains. Also has experience running developer-focused workshops (UC Berkeley computer architecture) and partnering with customer-facing stakeholders to drive adoption of a compliance-sensitive NLP product (SEC-aligned) at Penserra.”
Tianyi Wang
Entry-Level Backend/Cloud Engineer specializing in distributed systems and AI platforms
“Full-stack engineer with deep serverless AWS experience who built VidToNote, an AI video analysis platform, end-to-end using Next.js App Router/TypeScript and an event-driven pipeline (API Gateway, Lambda, DynamoDB, S3, Step Functions, SQS). Strong on production reliability and observability (CloudWatch, X-Ray, structured logging), plus data/analytics work in Postgres with measurable query optimizations and durable LLM evaluation workflows. Amazon background; integrated 22 AWS services and completed AWS Solutions Architect Professional certification within a month.”
Jacqueline Zhang
Mid-level Machine Learning Engineer specializing in LLMs, fairness, and healthcare ML
“ML/NLP practitioner with a master’s thesis focused on domain-adaptive knowledge distillation for LLMs (LLaMA2/sheared LLaMA), showing improved perplexity and ROUGE-L on biomedical data. Also built real-world data linking and search systems: integrated ClinicalTrials.gov with FAERS using fuzzy matching + embeddings, and delivered an LLM-powered FAQ recommender at Hyperledger using sentence-transformers, FAISS, and fine-tuning to mitigate embedding drift.”
Likhitha Bethi
Mid-level Software Engineer specializing in backend systems, distributed systems, and applied AI
“Goldman Sachs engineer who owned end-to-end features for an internal onboarding and case management platform, spanning React/TypeScript UI, a GraphQL gateway, and Node + Spring WebFlux microservices. Built and operated a Kafka-based ingestion and search pipeline with DLQs, retries, idempotency, and strong observability, and improved developer experience via backward-compatible GraphQL API design and schema-driven documentation.”
Dheeraj Kumar
Intern Data Scientist specializing in marketing analytics and data engineering
“AI/LLM practitioner with internships at Dell Technologies and Roche who built and deployed a healthcare-focused "Doctor LLM" by fine-tuning Meta Llama 3.2 on healthcaremagic.json, emphasizing safety guardrails to prevent harmful medical advice. Experienced in productionizing AI workflows with monitoring, testing, and orchestration (Airflow, Kubernetes), and in delivering AI-agent-driven competitive landscape insights to non-technical business stakeholders.”
Siddhik Reddy Kurapati
Junior Controls & Motion Planning Engineer specializing in MPC, RL, and autonomous systems
“Robotics researcher focused on learning-based navigation: builds sub-goal generation and cost-to-go models (Bayesian network-based) integrated with motion planning and MPC/NMPC control. Has hands-on ROS 2 package development across vehicles, drones, and manipulators, and uses a broad simulation stack (Isaac Sim, Gazebo, MuJoCo, PyBullet, PX4) to test and integrate systems.”
Syeda Sarah Shahrin
Mid-level Software Engineer specializing in AR/VR accessibility
“Spatial computing software engineer focused on making Apple Vision Pro/visionOS accessible, including building VoiceOver and Live Captions features. Debugged a complex Live Captions issue involving dual audio inputs during FaceTime screen sharing by leveraging iOS implementation docs and creating concurrent audio sources; also has safety-critical testing experience from train control systems and is interested in pivoting into robotics.”
Chris Du
Intern Full-Stack Software Engineer specializing in web apps and AI systems
“Product/UX designer who builds end-to-end systems across both consumer wellness and industrial/technical domains. Designed BloomPath (mental-wellness platform for therapists and young professionals) using research-driven, emotionally safe interaction patterns, and also simplified a Bosch autonomous parking vision-language mapping pipeline into a developer-facing real-time UI with layered debug tooling. Comfortable collaborating deeply with engineers and contributing in React/JS.”
Akshit Gaur
Mid-level AI Engineer specializing in agentic LLM systems
“Built and productionized a dual-agent LLM invoice-processing system for GFI Partners, adding guardrails and audit trails to earn stakeholder trust and drive adoption while cutting operational burden by 75%. Uses LangSmith observability to diagnose real-time workflow regressions and has experience teaching agentic AI concepts (e.g., at Carnegie Mellon) through hands-on, scaffolded demos.”
Lauren Corallo
Director of Supply Chain Transportation & ESG specializing in planning, procurement, and compliance
“Operations/business leader at Rent the Runway who led a cross-functional, Board-visible redesign and network-wide rollout of the company’s garment bag—a >$5M CapEx/OpEx initiative central to luxury customer experience. Known for aligning executives with conflicting priorities (cost vs CX), driving KPI-based operating rhythms, and delivering vendor/manufacturing wins that improved unit cost while upgrading product quality; previously led legal operations with strong confidentiality/privilege discipline.”
Swarnabha Roy
Mid-level Robotics & Computer Vision Engineer specializing in autonomous systems and edge AI
“Robotics/perception researcher (MVOS Lab, South Dakota State University) who built an end-to-end multimodal RGB-D + LiDAR pipeline for autonomous greenhouse harvesting and 3D plant phenotyping. Demonstrated strong production ownership by diagnosing motion blur with ROS-bag + OpenCV metrics and shipping an edge-deployed, scan-quality-aware workflow that boosted barcode read rate to 98% and supported ~70% autonomous pepper detection/harvesting accuracy.”
greg farhadian
Senior Software Engineer specializing in cloud data platforms and Java microservices
“Backend/data engineer with experience building Kafka-driven real-time pipelines that support ML code deployment and downstream integrations. Currently migrating high-throughput mainframe (COBOL/assembly) processing to Java, using Spark/Databricks to preserve performance and employing rigorous A/B testing across dev/pre-prod/prod with years of historical data.”
Daniel Luzzatto
Junior Machine Learning Engineer specializing in LLMs, computer vision, and robotics
“Built and deployed an agentic, multimodal LLM system that automates privacy redaction pipelines (audio/video/tabular) using LangChain orchestration and a closed-loop self-correction design. Personally implemented and performance-optimized core CV tooling (face blurring with tracking/Kalman filter) achieving >100 FPS on CPU, and validated reliability with golden-dataset benchmarking across 100+ privacy intents and measurable redaction metrics.”
Samuel Prabhakar Vara
Mid-level AI Engineer specializing in machine learning and healthcare research
“Backend engineer with end-to-end ownership of scientific and AI-powered systems, including neuron imaging pipelines at Monell Chemical Senses Center and an LLM-based structured information extraction platform for Wharton and PSG. Stands out for turning messy, compute-heavy workflows into reliable production backends with measurable impact, including saving researchers over 50 hours per week.”
Intern Machine Learning/Robotics Engineer specializing in computer vision and 3D simulation
Intern Technical Artist and Real-Time Rendering Developer specializing in Unreal/Unity and VR
Junior Machine Learning Engineer specializing in LLMs and retrieval-augmented generation