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Vetted Reinforcement Learning Professionals
Pre-screened and vetted.
Rajesh Nagula
Mid-level Robotics Software Engineer specializing in real-time control and perception
“Robotics software engineer focused on controls and motion planning for autonomous flight systems using ROS 2 (rclcpp), Gazebo/RViz, and BehaviorTree.CPP. Has hands-on real-time control experience (1ms loop rate) and has improved system performance by tracing latency issues and refactoring vision components (singleton camera init). Also built low-latency Ethernet/TCP comms on top of the IgH Ethernet stack and uses digital-twin simulation (Gazebo, MuJoCo; beginner Isaac Sim) to validate algorithms.”
Saisureshreddy Challa
Mid-level Data Scientist specializing in AI/ML, LLMs, and domain analytics
“BlackRock AI/ML engineer who built and owned a production LLM document intelligence system for regulatory and investment analysis end-to-end. They combined RAG, multi-agent validation, strong evaluation/monitoring, and reusable Python services to process 50K+ documents, cut review time 40-50%, and improve decision accuracy by about 25%.”
Ashutosh Jitendra Zawar
Mid-level AI/ML Engineer specializing in generative AI, NLP, and MLOps
“ML/AI engineer with hands-on ownership of production GenAI and computer vision systems, spanning experimentation, deployment, monitoring, and iterative optimization. Stands out for shipping an enterprise RAG platform that cut manual review by 50% and a defect detection pipeline that reduced report generation from 15 minutes to under 1 second while maintaining high uptime and strong operational discipline.”
Jake Arena
Mid-level growth marketer and producer specializing in entertainment and live events
“Startup-minded operator and event-business builder who created an outbound pipeline from scratch at Beat Repeat using POS and ticketing data, driving 30% higher repeat attendance and 15% lower costs. Also founded Drinklink, a bar subscription service sold face-to-face, and showed strong market instinct by identifying and negotiating an early strategic partnership with Posh before it was widely established in Los Angeles.”
Sumukh Porwal
Junior Robotics Engineer specializing in motion planning, controls, and autonomous aerial systems
“Robotics software engineer focused on autonomous eVTOL operations, including simulated autonomous ship deck landing using ROS2 Humble with perception (AprilTags) and motion planning under aircraft dynamics constraints. Has hands-on experience with multi-robot coordination, SLAM sensor-fusion fixes, and distributed robot networking (LTE + VPN), plus embedded data capture on Jetson AGX Orin and advanced control methods (MPC/CBF, differentiable learning).”
Agam Modasiya
Mid-level GNC Software Engineer specializing in robotics, autonomy, and controls
“Robotics software engineer with hands-on sim-to-real experience: built and deployed a reinforcement-learning vision policy at The Boring Company to align a robot end effector to tunnel lining engagement holes, owning the full pipeline (SolidWorks/URDF modeling, PyBullet + Stable-Baselines3 training, and on-machine deployment). Also modified ArduPilot and tested custom drone algorithms via ROS/Gazebo using MAVROS and VICON-based localization.”
Saikiran Gopalakrishnan
Senior Digital Twin & Simulation Engineer specializing in AI-driven manufacturing automation
“PhD-trained engineer with ~3.5 years of consulting experience building simulation/ML-driven manufacturing software. Deployed an ML surrogate model as a .NET C# DLL integrated with MES workflows, and resolved a critical pre-production latency issue by redesigning serialization/storage. Also built Python-based integrations across CAD/CAE tools and cloud material databases using an XML data model, with a strong interest in digital twins and real-to-sim/sim-to-real robotics workflows.”
Mihir Trivedi
Junior Machine Learning & Quant Research Engineer specializing in low-latency data and trading systems
“Applied ML to physical EV fleet systems at ST Labs, building a real-time CNN-LSTM fault prediction pipeline from streaming vehicle telemetry and addressing live data alignment issues via resampling/interpolation and buffered inference. Also developed a V2G/G2V energy transfer algorithm to automate charging/discharging for profit optimization, and made high-impact low-latency pipeline decisions at Astera Holdings using profiling, replay testing, and live A/B validation.”
Ludovic Morin
Entry-Level Machine Learning Engineer specializing in deep learning and statistical modeling
“Cornell master’s student (CS/Stats) focused on research-heavy ML projects: implemented a sparsity-driven RL approach (DAPD + Soft Actor-Critic) that maintained stable learning even with ~95% of weights removed in OpenAI Gym continuous-control tasks. Also worked on diffusion-based computer vision with conditioning and latency-focused U-Net choices, and scaled unsupervised community detection on a 50k-node/800k-edge Reddit graph via BFS subgraph sampling.”
Shao Rong Su
Senior AI Research Engineer specializing in LLM agents and predictive maintenance
“At Delta Electronics, partnered with automotive firmware teams to productionize an LLM-based coding assistant for identifying safety standard violations and generating bug-fix guidance. Built an agentic workflow with stepwise context extraction, similarity search, and a separate judge model for scoring reasoning/retrieval, and drove internal adoption through pain-point discovery and tailored technical demos using real firmware code.”
Akshit Modi
Mid-level AI/ML Engineer specializing in healthcare NLP and MLOps
“Healthcare/clinical ML practitioner who built and productionized ClinicalBERT-based pipelines to extract and standardize oncology EHR data, improving downstream model F1 from 0.81 to 0.92 while controlling training cost via LoRA/QLoRA. Experienced orchestrating real-time AWS ETL/ML workflows (Glue, Lambda, SageMaker) and partnering with clinicians using SHAP-based interpretability, contributing to an 18% reduction in readmissions and full adoption.”
Aditya Jaiswal
Intern Software Engineer specializing in cloud, DevOps, and applied AI
“Full-stack engineer with startup ownership experience (Aiir) building 15+ TypeScript/Go microservice APIs on GCP Cloud Run with Kafka-based async event streaming and React CRM integrations for billing/analytics. Strong post-launch operator who tuned Oracle performance (partitioning/indexing/query optimization) and validated a 23% retrieval-time reduction via AWR, and has a quality/DevSecOps mindset (94% Pytest coverage, GitHub Actions, SonarQube, Twistlock, CloudWatch) including migrating 18+ production CI/CD pipelines.”
Rifat Khan
Mid-level Mechanical/Aerospace Engineer specializing in scientific computing, CFD, and ML systems
“Robotics/control-focused engineer who built and validated a series elastic actuator control stack end-to-end (dynamic modeling, torque/position control, simulation, and experimental real-time debugging on hardware). Deep simulation background (OpenFOAM/COMSOL/Abaqus) and practical reproducibility tooling (Docker/CI), with conceptual ROS/ROS2 knowledge and confidence ramping into ROS-based stacks.”
Vaibhav Sharma
Mid-level Software Engineer specializing in AI/ML and data platforms
“AI/ML engineer who built a production agentic system to automate computational research experiments (simulation execution, parameter exploration, and numerical analysis) and mitigated context-window failures using constrained tool-calling/prompt-chaining patterns in LangChain with OpenAI tool-enabled models. Also has adtech/big-data pipeline experience at InMobi, orchestrating Spark jobs in Airflow to filter bot-like user IDs and publish clean IDs to an online NoSQL store for live serving, plus Apache open-source collaboration experience.”
Suloni Praveen
Entry-Level Software Engineer specializing in data engineering and ML systems
“Built an end-to-end Next.js/TypeScript LLM-based scientific PDF analyzer using local Ollama/Llama inference to prioritize privacy and cost, producing structured research artifacts (e.g., authors/methods/findings) with ~92% extraction accuracy. At Qualtrics, helped replace a batch pipeline with a real-time, low-latency ML inference service (Python/Go on Kubernetes) using Redis caching, Grafana-based observability, and graceful fallbacks to protect UX during failures.”
Michael Cohen
Executive Data & AI Leader specializing in enterprise SaaS and marketing analytics
“AI strategy and execution consultant currently doing contract/ad hoc work and planning to formalize the business with partnerships, GTM strategy, pro forma financials, and marketing/tech investments focused on AI productivity, governance, and security. Background includes founding startup teams, M&A/integration, and operating leadership in VC-backed scale-ups (Insight Ventures, EIP, Zetta Ventures) plus C-suite experience in a global PE-backed holding company, with 20+ years of published work in prediction and decision systems.”
Abdullah Muhammad
Mid-level analytics professional specializing in AI, strategy, and business intelligence
“Analytics-focused candidate with hands-on experience using SQL and Python to clean messy business data, automate reporting, and build practical customer analytics solutions. Notable examples include a 70% reduction in reporting time through Python-based Excel automation at Shell and stakeholder-friendly retention/RFM segmentation work for small business clients in freight and winery contexts.”
Atharva Bhide
Entry Software Engineer specializing in AI/ML and multimodal systems
“Built and shipped a production healthcare AI platform for a clinic in Brea, LA that combined LLM-based clinical report generation, voice agents for appointment workflows, and camera-based patient monitoring. Stands out for pairing multimodal AI architecture with production-grade reliability and compliance practices, while delivering concrete business results including 90% workflow automation, 200 hours saved per month, and a 60% improvement in customer retention.”
Mounika Musku
Junior Electrical Design Engineer specializing in power distribution and industrial automation
“Electrical design engineer with hands-on experience leading industrial and commercial building power systems, including a 4.16kV redundant distribution design for a 24/7 automotive supplier facility that was installed without shutting production down. Brings a strong mix of NEC-driven design rigor, analysis tools like AutoCAD Electrical/Revit/MATLAB, and field-oriented collaboration across controls, mechanical, commissioning, and contractor teams.”
Mounya Bonuga
Mid-level AI/ML Engineer specializing in multimodal AI and recommendation systems
“ML/AI engineer with hands-on ownership of a production LLM/RAG system at Goldman Sachs, focused on workflow automation and large-scale document search for operational teams. They combine strong MLOps and backend engineering skills with practical GenAI evaluation and safety practices, and cite measurable impact including 22% better task guidance accuracy and sub-second search across millions of records.”
Sanjay Jayalakshmi Prabakar
Mid-level Robotics Engineer specializing in surgical robotics, teleoperation, and reinforcement learning
“Robotics software engineer with hands-on experience across reinforcement learning and ROS/ROS2, including a project teaching Boston Dynamics Spot to open a door by combining vision-based pose estimation with SAC-trained IK and a walking policy in MuJoCo. Previously built ROS Noetic control for surgical robots using RCM with MoveIt IK and achieved sub-0.02s latency via threading; also participated in a NASA ROS2 space simulation building rover teleop and sensor-driven mapping.”
Sreekar Praneeth Marri
Junior Robotics & AI Researcher specializing in soft robotics and real-time ML control
“Early-career robotics engineer who has integrated LLM/NLP command interfaces (OpenAI/LLaMA) into ROS-controlled industrial manipulators and built data-driven controls for underwater soft robotic actuators. Combines hands-on fabrication (balloon actuator with embedded copper traces) with sensor debugging (IMU/Aurora) and simulation work in Gazebo, with practical exposure to edge deployment constraints on Jetson Nano and model quantization.”
Neha Navarkar
Junior Robotics Engineer specializing in autonomous navigation and SLAM
“Robotics software engineer who owned the end-to-end navigation stack for a mobile manipulation robot (Cone-E), integrating ZED-2i SLAM into a real-time occupancy grid with live obstacle avoidance, A* planning, and lookahead control. Strong in real-time debugging and stability improvements (goal snapping/locking, obstacle persistence, rate-limited replanning) and validates changes on hardware, supported by simulation (Gazebo/Webots) and Docker/CI-based testing.”
Anil Kircaliali
Director-level Robotics Engineer specializing in robotic additive manufacturing and digital twins
“Head of Robotics at Orbital Composites who built the full ROS-based software stack ("OrbOS") for multi-robot KUKA-arm 3D printing of carbon-fiber composite geometries. Deep in motion planning and real-time control—created a pipeline to turn underconstrained toolpaths into optimal joint trajectories at massive command scale, plus redundant safety gatekeeping and a 250Hz synchronized robot+extruder controller. Has operated in a technical-founder capacity for ~6 years and values an engineering culture of openness, honesty, accountability, and high ownership.”