Vetted Reinforcement Learning Professionals

“ML/LLM engineer who has built and productionized a large multimodal LLM pipeline end-to-end—fine-tuning a 20B+ parameter model with distributed/FSDP training and deploying on Kubernetes via Triton for ~5x throughput. Strong focus on reliability and safety (monitoring with SHAP, guardrails, A/B testing) with reported ~22% relevance lift and reduced harmful/incorrect outputs, plus experience orchestrating ETL/retraining workflows with Airflow across S3/Snowflake/RDS.”

“VC-focused sourcing candidate with a multi-channel approach spanning technical research communities (GitHub/arXiv/Hugging Face) and LinkedIn, plus access to founder networks like NVIDIA Inception. Has experience initiating cold founder relationships and progressing them through intro calls into deeper technical and business diligence, with a structured weekly pipeline/partner update cadence and thematic notes on frontier technologies.”

Rakshak Shah

Screened

Intern Software Engineer specializing in cloud, AI, and systems programming

Seattle, WA1y exp

“AWS intern who significantly evolved a Drift Audit Service backend (Control Tower/EventBridge context) to make drift findings more explainable and reduce false positives by adding a verification step in Lambda before event ingestion. Demonstrates strong API design fundamentals in Python/FastAPI (contracts, idempotency, security controls) and careful rollout practices (feature flags, canaries, phased deployments).”

“Robotics software engineer/researcher with hands-on experience building a MuJoCo-based digital twin of a 6DOF soft-actuated manipulator, spanning robot design, custom actuator dynamics, classical control (PID/MPC), and RL (imitation learning and TD-MPC2 model-based RL). Also has ROS1-in-Docker SLAM integration/visualization experience and delivered a major trajectory-tracking improvement (error reduced from ~100mm to ~5mm) via Savgol smoothing, plus prototype fleet communications work for a solar-powered power line inspection robot.”

“Robotics engineer who worked on a lunar rover program, building a simulation environment that mirrored real hardware interfaces and incorporated moon-terrain slip/friction modeling validated against a physical “moon yard.” Also integrated an ML-based munition X-ray inspection system via REST APIs, deploying and scaling inference on Azure with Kubernetes plus Prometheus monitoring, load balancing, and self-healing reliability mechanisms.”

“Embodied AI/robotics ML engineer with hands-on experience deploying POMDP-based reinforcement learning controllers on real mobile robots and vehicle fleets. Strong in sim-to-real robustness (domain randomization) and production rollout practices (HIL, shadow-mode, canaries, safety instrumentation), and has published related work (mentions a NeurIPS paper).”

Seongjae Ahn

Screened

Intern/Junior Robotics & Controls Engineer specializing in simulation, teleoperation, and diffusion policies

Berkeley, CA2y exp

“Robotics software engineer focused on simulation-to-teleoperation pipelines in NVIDIA Isaac Lab/Isaac Sim, including custom Dynamixel motor control integrated with USD/physics for dataset collection. Has hands-on ROS2 Humble + MoveIt2 integration for UR + Robotiq in Omniverse and builds Docker/CI workflows for GPU-enabled robotics stacks; also brings MPC coursework and multi-robot ocean drone comms experience (XBee/I2C).”

“ML/robotics engineer with Apple experience who built a computer-vision-driven industrial defect detection system integrating a robotic arm with ROS-based real-time inference on an edge GPU. Drove major performance gains (cut inference time ~60% via quantization + TensorRT) and improved robustness to lighting/material variation, with strong emphasis on production reliability (health checks, watchdogs, observability, CI/CD) and interest in shaping early-stage startup engineering culture.”

Greta Skousgard

Screened

Senior Change Management & Recruiting Leader specializing in global adoption and talent operations

New York City, NY17y exp

“People leader with large-team management experience (15 direct reports) and recruiting leadership responsibilities (4 indirect) spanning onboarding, coaching, performance management, and KPI delivery. As a Sr Recruiter, stepped in as a change facilitator to turn around adoption of a new scheduling system, boosting engagement by 50%+ through retrospectives and working sessions. Also partnered with senior leadership at McKinsey on AI product adoption communications to drive alignment across functions.”