Asias leading robotics solutions provider, automating enterprise supply chains since 2017. We build syncOS — the industry-first no-code platform that lets manufacturers and warehouse operators integrate, reprogram, and scale automation systems without halting production or calling in specialists. Our autonomous mobile robots (AMRs) run 24/7 for global brands like Ford, Coca-Cola, and Kimberly-Clark — transforming production lines in hours, not weeks.
We started as roboticists ourselves. We know the pain of fragmented, proprietary systems that refuse to talk to each other. syncOS is our answer — and we believe its what the industry has been waiting for. We are a young, passionate team chasing one big mission: #automateasia. If you love robots, hate inefficiency, and want to build solutions that run on real factory floors — read on.
KEY RESPONSIBILITIES:
Owner of the algorithms that decide how the fleet moves - task allocation, routing, and traffic management across every AMR on site.
Turn multi-robot coordination problems into algorithms that hold up under real site load, and prove it with data, not intuition.
Task allocation, end to end - You design and maintain the algorithms that decide which AMR takes which job, balancing throughput, battery state, and site layout across the fleet.
Traffic and conflict resolution - You own the logic that keeps AMRs from colliding, deadlocking, or queuing badly at shared paths, intersections, and pick/drop points - across every MAG AMR variant and lifter generation in the fleet.
Routing and path optimization - You build and tune the routing algorithms that get robots from A to B efficiently, adapting to site-specific layouts and constraints.
Algorithm quality under real load - You validate changes against simulated and live fleet data before they ship, so a fix for one site doesnt regress another.
Instrumentation and tuning - You build the metrics and tooling to see how the fleet is actually performing (throughput, congestion, idle time) and use them to tune the algorithms, not guesswork.
Collaboration on the interface - You work with the platform and robotics teams to keep the algorithm layer working cleanly against the AMR-syncOS interface contract.
You will partner closely with:
Fleet manager team lead: on what problem to solve next and how it fits the fleet manager roadmap - they set priorities, you own the algorithm design.
Platform engineers (Integrator, dashboard): on the APIs and data your algorithms depend on and expose.
Robotics Engineering: on the AMR-syncOS interface contract - what the fleet manager can assume about robot behavior, and what it must account for across AMR variants.
Quality: who independently test and certify releases - you build to the bar, they verify it.
WHAT DOES SUCCESS LOOK LIKE FOR THIS ROLE
3 months:
Shipped your first change to fleet manager algorithm logic into a live customer environment
Fluent in how task allocation, routing, and traffic management work today across the fleet
Able to reproduce and diagnose a reported fleet-behavior issue (e.g. congestion, bad allocation) end to end
Working directly with the fleet manager team lead with minimal ramp-up friction
6 months:
Owning a defined algorithm area (e.g. traffic management or task allocation) with minimal oversight
Built or improved the simulation/backtesting tooling used to validate algorithm changes before ship
Trusted to review other engineers changes to fleet manager algorithm code
Tuned an algorithm against live site data with a measurable throughput or congestion improvement
12 months:
A recognized go-to engineer for fleet manager algorithms
Your algorithm changes ship across multiple sites with minimal live-site escalations
Contributed a reusable improvement (tooling, technique, or component) that other algorithm work builds on
Mentoring newer engineers joining the fleet manager team
6 years of software engineering experience with real, hands-on work on algorithmic problems (scheduling, routing, graph search, optimization, or similar).
Strong CS fundamentals - data structures, algorithms, complexity analysis - and the ability to reason about correctness under concurrency.
Experience with simulation, backtesting, or data-driven validation of algorithm changes before they ship.
Exposure to multi-agent or multi-robot systems, path planning, or traffic/scheduling problems is a strong plus, not a requirement.
Proficiency in at least one systems language (e.g. Python, C++) used to implement and productionize algorithms.
Comfort operating in a fast-moving startup building for real industrial customers.
Competitive salary
Comprehensive health benefits package
Hustle of a young startup, always something to do and something to improve
Opportunities for professional development and growth into management roles
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