live-deployedEdTech/trainingSIRENA TECHNOLOGIES PVT LTD
Robotics & Physical AI Trainer — SKIP-X
School of Robotics & Artificial Intelligence, Sirena Technologies
- Reports To - Head of SKIP-X
- Location - Bangalore (on-site; lab/studio based)
- Function - SKIP-X Delivery — Training & Curriculum Execution
- Preference - Prior experience in EdTech / training delivery preferred
About SKIP-X
SKIP-X (Sirena Knowledge & Innovation Program) is Sirena Technologies' vertically integrated Robotics and AI education ecosystem, spanning school outreach (Ignite), undergraduate engineering integration (Evolve), a 12-month postgraduate residency (Mastery), and a parallel Research track. Unlike conventional robotics courses built on simulations or toy kits, SKIP-X trains learners on Sirena's own commercial robot platforms — the same hardware the company manufactures and deploys with enterprise clients globally.
Role Purpose
The Trainer is the primary face of SKIP-X in the classroom and lab. This is a generalist role: the Trainer will deliver hands-on instruction across all five SKIP-X platform tracks — Humanoid Robotics, Quadruped Robotics, Manipulation Robotics, Autonomous Systems, and Physical AI & Human-Robot Interaction — adapting depth and pacing across the Ignite, Evolve, and Mastery cohorts.
Key Responsibilities
- Hands-on delivery: Conduct lab-based sessions across all SKIP-X platforms — Nino (humanoid), Twist/Perro (quadruped), robotic arm (manipulation), UBOT (autonomous mobile), and Nina (HRI/Voice AI) — covering assembly, programming, and applied problem-solving.
- Curriculum execution: Deliver structured content across the 12-session Ignite curriculum, the 8-semester Evolve track (digital electronics, ROS2, SLAM, reinforcement learning, multi-robot systems), and Mastery's 4-phase residency (modeling/simulation, embedded hardware, autonomy, industry contribution).
- Technical breadth: Teach across ROS2/ROS Humble, Gazebo simulation, computer vision (YOLO, OpenCV), embedded systems (micro-ROS, PID control, FreeRTOS), SLAM and navigation (Nav2), reinforcement learning (Isaac Lab), and applied LLM/agentic AI on robotics platforms.
- Daily/weekly lab structure: Run concept-and-demo sessions, supervise lab builds, enforce daily Git/code submission discipline, and conduct mandatory hardware demo reviews (no slide-only sessions, per SKIP-X philosophy).
- Assessment and certification: Evaluate student deliverables — working code, functioning hardware builds, GitHub portfolios — against SKIP-X's outcome standards (4+ robots built, ROS2 proficiency, AI stack deployment).
- Student progression support: Support learners across entry points — school students with no prior experience through to engineering graduates and professionals in the Mastery residency — adapting instruction without diluting the build-don't-simulate standard.
- Content and platform updates: Stay current with Sirena's commercial robot platform updates (firmware, SDK, AI stack changes) since training content mirrors live deployed hardware.
- Cross-functional coordination: Work with the Head of SKIP-X and curriculum team to align session delivery with CoE partner timelines, university semester calendars, and Mastery cohort schedules.
Candidate Requirements
- Technical foundation: Strong working knowledge of robotics fundamentals — kinematics, control systems, embedded programming (C/C++, Python) — and at least working familiarity with ROS2, computer vision, and one of: SLAM, reinforcement learning, or HRI/voice AI.
- Hands-on credibility: Demonstrated experience building or programming physical robots (not simulation-only); portfolio of hardware projects, competitions, or research work is a strong plus.
- Teaching ability: Prior experience training, teaching, or mentoring — classroom, lab, bootcamp, or corporate training settings — with the ability to adapt explanations across skill levels from school students to working engineers.
- EdTech experience (preferred): Candidates with prior experience in EdTech, training delivery, or curriculum-based instruction will be preferred, given the structured, outcome-driven, cohort-based nature of SKIP-X delivery.
- Education: B.Tech/M.Tech in Robotics, Mechatronics, Electronics, Computer Science, or related field; equivalent practical experience considered.
- Disposition: Comfortable working in a fast-paced, build-first lab environment; patient and structured with first-time learners; rigorous with advanced cohorts.
Pay: ₹30,000.00 - ₹50,000.00 per month
Work Location: In person
