Pre-screened and vetted.
Junior Software Engineer specializing in backend APIs and ML-driven systems
“Internship experience at Paycom owning an end-to-end personalized course recommendation feature for an LMS, spanning SQL-based data pipelines, ML integration, and FastAPI REST services for real-time recommendations. Focused on production tradeoffs (latency vs. accuracy), scaling/SQL optimization, and post-launch iteration driven by engagement metrics.”
Mid-level Software Engineer specializing in Generative AI automation and secure platforms
“Backend/security-focused engineer from VeroTX who built an IdP service (Spring Boot + MongoDB on GCP) for an AI workflow platform and drove major latency improvements via caching and query/index optimization. Also shipped an AI loan-processing agent using LangChain/LangGraph, owning the document ingestion + vector database layer and designing a reliable multi-step workflow with retries, monitoring, and human-in-the-loop safeguards.”
Junior Software & ML Engineer specializing in cybersecurity and data-driven systems
“Software development intern who owned and shipped a production-used WeChat mini-program (JavaScript + MongoDB) serving ~3,000 users in a semester. Emphasizes maintainable UI architecture through modular, reusable components and clear separation between UI presentation and data/business logic, with a performance mindset (caching/reducing redundant updates).”
“Game design capstone project owner who built and tuned a full steal/sell/upgrade progression economy for a house-robbery game, including item weight/value balancing, upgrade pacing, and difficulty gates (police/NPC detection). Iterated via playtests and basic telemetry signals (purchase rates, item selection) and implemented a code-driven item attribute system to speed tuning, while also negotiating scope tradeoffs with the team around adding minigames.”
Mid-level Software Engineer specializing in AI RAG systems and full-stack cloud applications
“AI/LLM engineer who shipped a production RAG-based knowledge assistant at SparkPlug serving 10,000+ daily users, streaming GPT-4 answers with inline citations over WebSockets. Demonstrated measurable impact (support resolution time cut 18→12 minutes; retrieval precision +~20%) and strong production rigor across ingestion, monitoring/alerting, evaluation, and messy ERP-style data integration with validation, RBAC, and idempotent operations.”
Mid-level Data Engineer specializing in cloud data pipelines and Snowflake
“Data engineer who has owned production pipelines end-to-end, ingesting 50–100 GB/day from APIs/S3 and near-real-time Kafka into Snowflake with strong data quality gates (Great Expectations/dbt) and Airflow-based reliability (SLAs, alerting, dashboards). Also built a Snowflake-backed REST data API with caching/pagination and versioned endpoints, and designed a compliant, scalable web-scraping system with anti-bot handling and safe backfills.”
Director-level Talent Acquisition leader specializing in data-driven and AI-enabled recruiting operations
“Recruiting leader who has managed a 23-person team and drives performance through servant leadership, coaching, and recognition. Partnered with HRBPs on employee-care initiatives to embed assessments/certifications and improve team capability, and successfully pitched the CEO to build a dedicated LinkedIn Recruiter/social media sourcing team that delivered results within months.”
Intern Product & Project Management professional specializing in analytics-driven delivery
“Product Management Intern who owned an end-to-end sourcing-style initiative for a new digital product launch, coordinating internal stakeholders and external vendors. Uses data-driven, value-focused negotiations and milestone-based delivery management (Jira/Smartsheet) to control scope, timelines, and supplier performance while proactively mitigating cost and schedule risks.”
Junior AI Engineer specializing in Generative AI, RAG, and NLP
“AI/LLM engineer who has shipped a production RAG platform at Ticker Inc. on GCP (Qdrant + Postgres) delivering sub-second retrieval over 550k+ items, with measurable gains in latency and answer quality (HNSW optimization, MMR re-ranking). Also built an asynchronous LangChain/LangGraph multi-agent research system (10x faster cycles) and partnered with Indiana University doctors on synthetic patient records and ML error analysis using clinician-friendly F1/loss dashboards.”
Mid-level AI/ML Engineer specializing in LLMs, RAG, and production inference
“AI/LLM engineer who built a production resume-parsing and candidate-matching platform at Quadrant Technologies, combining agentic LangChain workflows, VLM-based document template extraction (~85% accuracy), and a hybrid RAG backend for resume-to-JD search. Notably integrated automated LLM evals and metric-based CI/CD quality gates to catch silent prompt/model regressions, and led a 3-person team across frontend/backend/testing.”
Mid-level AI Engineer specializing in causal inference and LLM research
“LLM engineer who has deployed a production system combining LLMs with causal inference (DoWhy) to enable counterfactual “what-if” analysis for experimental research, including a robust variable-mapping/validation layer to reduce hallucinations. Also partnered with non-technical operations leadership at Irriion Technologies to deliver an AI-assisted onboarding workflow that cut onboarding time by 50% and reduced manual errors by ~40%.”
Senior Product Marketing Manager specializing in GTM, channel enablement, and pricing analytics
“Growth-creative/performance creative specialist focused on UGC-led paid social across Meta, TikTok, and YouTube. Uses structured creative testing (e.g., hook/angle matrices) and modular asset systems to iterate quickly; cited a campaign that lifted efficiency (25% CPA improvement, ROAS 1.8x→2.4x) and then scaled spend ~60% while maintaining performance.”
Entry-Level Full-Stack Software Engineer specializing in serverless AWS and AI applications
“Built and deployed serverless AWS applications (Lambda/S3/RDS Proxy) including a NASA L’Space React + Python data analysis tool, focusing on performance for large datasets. Demonstrates strong cloud troubleshooting across compute and networking (CloudWatch-driven diagnosis, EC2 scaling, security group fixes) and a user-driven iteration loop that improved product usability with dynamic filtering and interactive UI.”
Mid-level AI/ML Engineer specializing in Generative AI and LLM-powered NLP
“LLM/AI engineer who built a production automated document-understanding pipeline on Azure using a grounded RAG layer, designed to reduce manual review time for unstructured financial documents. Demonstrates strong real-world scaling and reliability practices (Service Bus queueing, Kubernetes autoscaling, observability, retries/circuit breakers) plus rigorous evaluation (shadow testing, replaying traffic, multilingual edge-case suites) and stakeholder-friendly, evidence-based explainability.”
Mid-level Machine Learning Engineer specializing in computer vision and reinforcement learning
“Early-stage engineer with hands-on embedded prototyping experience (Arduino/Raspberry Pi) who helped build an award-winning smart glasses project enabling phone notifications via Bluetooth. Strong computer vision performance optimization background, including accelerating 120 FPS inference by moving from TensorFlow to PyTorch and deploying through ONNX + TensorRT quantization, plus Docker-based GPU deployment and CI/ML practices.”
Entry-Level Software Engineer specializing in full-stack and machine learning
“Robotics software builder who delivered an end-to-end gesture-controlled drone system using an ESP32+IMU stream and real-time ML inference mapped to Tello SDK commands. Drove reliability improvements by instrumenting the pipeline with timestamps/logging and matching training vs runtime preprocessing, reaching ~94% gesture classification accuracy; experienced with Docker/Compose for reproducible multi-service deployments.”
Mid-level Software/Systems Engineer specializing in Python, Linux, and network testing
“Entrepreneurial product builder who has shipped two live App Store apps (Pixo content-based product marketing platform and Clutch AI dating reply helper). Also helped build a real-estate seller platform end-to-end, using AI matching to find buyers and contributing to onboarding nearly paying users and generating active MRR.”
Intern Software & AI Engineer specializing in distributed systems and LLM applications
“Stony Brook Fall 2024 capstone contributor who built a ROS2-based warehouse mobile robot prototype, owning perception and SLAM integration end-to-end. Strong in real-time robotics optimization on Jetson Orin (TensorRT/CUDA, ROS2 tracing/Nsight) and in distributed ROS2 communications (DDS discovery/QoS, MAVLink-to-ROS2 bridging), with a full simulation/testing/deployment toolchain (Gazebo, CI tests, Docker/K3s).”
Senior Backend Software Engineer specializing in Java, microservices, and cloud infrastructure
“Backend/platform engineer at Aryaka Networks who built a centralized resiliency and security Spring Boot library to standardize Keycloak RBAC and fault-tolerance across 25+ Kubernetes-migrated microservices. Uses profiling and observability (Prometheus/Grafana) to drive measurable performance and reliability gains (25% faster APIs, 70% faster environment setup) and accelerates adoption via golden-path starter repos and Swagger/OpenAPI live docs.”
Mid-level AI Engineer specializing in Generative AI and multimodal RAG systems
“GenAI/LLM engineer who built and productionized a 0-1 application (EMULaiTOR at Lumanity) combining qualitative + quantitative data using Postgres/pgvector RAG and prompt engineering, deployed with Azure backend and AWS-hosted frontend. Demonstrates strong production instincts (latency reduction via region alignment, autoscaling/health checks) and hands-on agent/tool-call debugging, plus experience enabling sales and winning a large pharma client.”
Mid-level Full-Stack Software Engineer specializing in Healthcare and Insurance platforms
“Full-stack engineer with healthcare and insurance domain experience who has owned production systems end-to-end (React/Next.js, FastAPI/Node, Postgres, AWS SNS/SQS, Docker, CI/CD) and delivered measurable impact (30% faster data processing). Also productionized an LLM-powered clinical data assistant using RAG + a vector database with guardrails and evaluation loops, cutting analyst lookup time by ~30–40%, and has experience modernizing monoliths to microservices with feature-flagged, low-regression rollouts.”
Entry-Level Backend Engineer specializing in analytics automation and cloud data pipelines
“Forward Deployment Engineer focused on application security and production integrations, with hands-on experience hardening API-driven ticketing systems (JWT/RBAC/rate limiting/log redaction) and implementing CI/CD security controls (Bandit SAST, SCA, container hardening). Strong in diagnosing peak-load production issues using logs/metrics/infra signals and driving durable fixes like adaptive throttling and backoff, while aligning engineering, business, and leadership stakeholders on risk and SLA impact.”
Mid-level Full-Stack/MES Software Engineer specializing in manufacturing systems
“Software engineer with hands-on experience delivering production-floor applications in manufacturing environments: built a PDA-friendly web app integrated with Oracle PL/SQL and deployed it on-site in a live warehouse, then iterated via tight feedback loops. Also rebuilt a broken assembly QR label printing workflow as a WPF Windows desktop tool and rolled it out across factory processes with operator training; additionally built a TypeScript/Node/Express/MongoDB app deployed on AWS (EC2/S3).”
Mid-Level Technical Game Designer and Game Developer specializing in VR and Unity
“Unity/C# developer with shipped VR multiplayer experience (Photon, server-authoritative networking) including a safety-critical VR title (Swashbuckler at GrooveJones). Built a runtime content pipeline that loads Photoshop files from StreamingAssets and auto-preps basic animations, letting artists iterate in-engine without touching the Unity project—dramatically accelerating asset creation and increasing the volume of illustrated content.”