Pre-screened and vetted.
Mid-level Solutions Engineer specializing in ads platforms and ML-driven marketing systems
Mid-level AI/ML Engineer specializing in LLM training, RAG, and low-latency inference
Senior Machine Learning Engineer specializing in GenAI, NLP, and recommendation systems
Senior DevOps/SRE Engineer specializing in cloud infrastructure and CI/CD automation
Director of Platform specializing in go-to-market and portfolio value creation
Senior AI Engineer specializing in machine learning, NLP, and generative AI
Executive Technology Leader (CTO/COO) specializing in Telecom, IT Delivery, and eGovernment platforms
“Entrepreneurial operator who has started three revenue-generating startups for an employer and is now ready to found independently. Built and scaled a USSD-based lottery product in Nigeria by partnering with MTN, driving 10%+ uplift in gross turnover, and has hands-on experience validating market gaps via SMS/call-center surveys and launching pilots before scaling.”
Intern Software Engineer specializing in distributed systems and cloud infrastructure
“Built and operated a production warehouse metadata collection platform at Sigma Computing, integrating Go/gRPC services with a TypeScript backend and MySQL, with strong emphasis on idempotency, retries, bounded-concurrency job queues, and Datadog-based observability. Also created Kurral (kurral.com), an AI agent runtime security and observability/governance SDK/proxy concept, iterating via pilot-customer feedback and market research; targeting founding engineer roles with $180–200k base and ~2–5% equity.”
Entry-level Software Engineer specializing in full-stack and AI systems
“Frontend-leaning full-stack engineer who described owning an artist search and detail experience across UI, backend integrations, and data modeling. They show practical strength in scalable React architecture, TypeScript safety, and performance tuning, with a product-minded approach to shipping 0→1 features quickly and iterating after launch.”
Mid-Level Software Engineer specializing in cloud infrastructure and full-stack web development
“Backend engineer at Electric Hydrogen who built a serverless device-log ingestion and processing platform in Python/Flask, scaling throughput (4x peak ingestion) while keeping sub-300ms API latency. Strong in Postgres/SQLAlchemy performance (partitioning, materialized views) and production ML integration (ONNX model served via FastAPI microservice with async batch inference, Redis feature caching, and drift monitoring via S3/Lambda). Experienced designing secure multi-tenant systems with schema-per-tenant isolation and KMS-backed encryption.”
Senior Software Engineer specializing in FinTech and distributed systems
“Backend/AI engineer who has built a rule-service platform on AWS and evolved it into an agentic RAG system using LangChain, ReAct, tool calling, and LLM-as-judge review. Notable for combining heavy AI-assisted development with production safeguards like manual CR, CloudWatch monitoring, fallback strategies, benchmark testing, and user-feedback-driven model improvement.”
Junior Software Engineer specializing in backend systems and AI/ML pipelines
“Robotics-focused engineer with ROS 2 experience who has built and debugged real-time, distributed control/orchestration systems under production-like latency and safety constraints. Led platform changes at Persona for a real-time verification orchestration system using deterministic state machines and async workers, and has hands-on experience stabilizing multi-robot navigation/SLAM behavior using rosbag, RViz, and stress testing in simulation (Gazebo).”
Engineering Manager specializing in AI/ML platforms and 0→1 product delivery
“Player-coach engineer/lead on a high-scale research integrity platform ("Lighthouse") that flags fraud/manipulation signals across ~3M academic manuscripts per year. Owns architecture decisions (ADRs), implements across Go/Java/React services, and introduced NLP (SciBERT embeddings + human-in-the-loop) to assess out-of-context citations while also handling production incidents with a data-consistency-first approach.”
Mid-Level Full-Stack Software Engineer specializing in distributed systems and cloud-native microservices
“Backend engineer (4 years) who built an end-to-end Python backend for a patent-pending in-car massager/heater system, including GraphQL data modeling and Bluetooth integration with an ESP32 microcontroller (reverse engineered a niche protocol). Also has strong platform experience: on-prem Kubernetes/CI-CD (Jenkins/GitLab, exploring ArgoCD GitOps), Terraform-based infra workflows, a RabbitMQ messaging library used across microservices, and an on-prem migration of ~30 critical applications with rollback/parallel-run strategy.”
Intern Software Engineer specializing in AI agents, RAG pipelines, and semiconductor systems
“Built a web-based interface that connects an internal bug system to an LLM for initial debugging and issue classification, aiming to boost QA and software engineer efficiency while balancing latency and accuracy. Worked as a one-person project and managed constraints like limited hardware and difficulty extracting team debugging context, relying on manager communication and rapid modeling to validate direction.”
Junior Robotics & Reinforcement Learning Engineer specializing in dexterous manipulation
“Robotics software engineer (master’s student) who placed 3rd in the CMU VLA challenge and presented at IROS, building an LLM-powered language system (Gemini 2.5) for mobile-robot scene Q&A and language-based navigation. Hands-on ROS1/ROS2 experience including ros2_control + PILZ planning for a KUKA arm, plus simulation (Gazebo) and containerized submissions with Docker.”
Junior Mechanical Engineering & Software Developer specializing in aviation autonomy and retrieval systems
“Robotics/embedded builder who trained an aviation-specific LLM and deployed it offline on an NVIDIA Jetson for an in-flight voice assistant, solving performance and cabling constraints with NVMe storage and Bluetooth. Also has hands-on Raspberry Pi/Arduino robot builds (including a cigarette-butt picking prototype with hydraulic actuation) plus Docker-based FEA work using FEniCS/Gmsh and strong CI/CD + automated testing practices.”
Intern Software Engineer specializing in robotics, autonomous vehicles, and embedded AI
“Robotics software engineer with internship experience at John Deere and AeroVironment, working across C++/Python stacks and ROS2-based systems. Drove a proof-of-concept migration from an x86/FPGA target to NVIDIA GPU solutions and helped turn a hackathon prototype into a production-ready, CI/CD-driven build-and-deploy workflow with comprehensive automated testing.”
Junior Software/ML Engineer specializing in AI systems, cloud infrastructure, and applied research
“Backend/infra-focused engineer with experience spanning Go-based MCP servers for an AI-assisted Kubernetes on-call diagnosis chatbot and a Python/Flask PagerDuty automation integration. Previously at Tesla, optimized high-volume battery test data in PostgreSQL using JSONB, partitioning, and a timestamp normalization pipeline; also built PyTorch PINN training workflows and achieved a 20x speedup via batch vectorization.”
Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable inference
“Backend/retrieval-focused engineer with production experience at Perplexity building a large-scale real-time Q&A system using retrieval-augmented generation, emphasizing low-latency, high-quality answers through ranking, context optimization, and caching. Also has orchestration experience from both product-facing LLM pipelines and large-scale infrastructure workflows at Meta, and has partnered with non-technical stakeholders to align AI trade-offs with business goals.”
Intern Robotics Engineer specializing in robot learning, SLAM, and control
“Robotics architect intern/new-grad focused on warehouse AMRs, building ROS2 sensor-fusion and SLAM stacks (FastSLAM-style particle filter) and validating in Gazebo with ground-truth metrics. Also interned at ASML debugging real-time in-vacuum robot behavior via Python state-machine telemetry scripts, identifying a firmware driver issue impacting throughput.”