Total 5 job vacancies by Ability Robotics Pte. Ltd.

About Us:

Phridom AI - Ability Robotics is an early-stage robotics and AIcompany building the core systems behind embodied intelligence. Ourtechnologies help robots understand the physical world, learn intelligentbehaviours, and operate reliably in real environments. We’re still in stealth,but we’re already working with a select group of partners to validate oursystems in high-impact robotics applications. If you're excited to buildfoundational technologies for the next generation of robotics and wantmeaningful ownership over hard technical problems, we'd love to hear from you.

Role Overview:

As a Simulation & Synthetic Data Engineer, you’ll build thesimulation and data infrastructure that helps embodied robots learn, test, andimprove before they reach the real world. Your work will accelerate modeldevelopment, strengthen sim-to-real reliability, and directly support robotdeployments in customer environments.

What you'll work on

1.                         Develop and scale robotic simulation environments for algorithmvalidation, system testing, and data generation.

2.                         Design simulation scenarios and task environments that supportperception and learning model training and evaluation.

3.                         Build automated synthetic data generation pipelines with controllablescenario variation and domain randomization.

4.                         Collaborate with perception and learning teams to define datarequirements, benchmarks, and evaluation metrics.

5.                         Improve alignment between simulation and real-world systems tosupport sim-to-real transfer.

6.                         Develop tooling that improves the efficiency, reliability, andscalability of data generation workflows.

7.                         Align simulation interfaces and workflows with real robot systemarchitectures.

Technical Requirements

Must Have

1.                         Bachelor's degree or above in Robotics, Computer Science, Graphics,Simulation, or a related field, with at least 3 years of industry experience.

2.                         Experience with at least one robotics simulation platform (e.g. IsaacSim, MuJoCo, Genesis, Newton, etc.).

3.                         Strong Python programming skills.

4.                         Solid understanding of robotic systems, perception, and controlfundamentals.

5.                         Strong systems thinking and engineering execution capabilities.

6.                         Ability to independently build simulation environments and automateddata generation workflows.

7.                         Familiarity with GPU acceleration and parallel computing technologies(e.g. CUDA, PyTorch, TensorRT).

Nice to Have

1.                         Experience working with humanoid robots, mobile manipulators, orother robotic platforms.

2.                         Experience building large-scale synthetic data generation systems.

3.                         Familiarity with photorealistic rendering pipelines.

4.                         Familiarity with latest developments in robotic simulation space.

5.                         Experience with sim-to-real techniques, domain randomization, orrelated approaches.

6.                         Experience collaborating closely with machine learning or robotlearning teams.

7.                         Experience building reproducible simulation and experimentationpipelines.

Your Impact

•                             Your work will ship into real deployments, helping humanoid andembodied robots operate reliably in customer and public environments - not justcontrolled demos.

•                             You'll improve system robustness across both simulation and physicalhardware under real-world conditions.

•                             You'll help transform prototypes into scalable, repeatable systemsthat improve uptime, safety, and data quality across deployments.

•                             You'll play a key role in accelerating how quickly the team canbuild, test, learn, and deploy.

Why Join Us

Join us at an early stage and help build the core softwareinfrastructure behind humanoid and embodied robotic systems heading towardreal-world deployment. We move fast, ship often, and give engineers meaningfulownership—so you'll learn quickly, tackle high-impact challenges, and see yourwork running on real robots outside the lab. With active business across Chinaand beyond, you'll gain unique exposure to global robotics ecosystems,customers, and partners as the company scales.

Location

This role is based on-site in Singapore, working closely with theengineering team and robotic systems.

Occasional international travel to China and other regions may berequired for training, customer engagements, deployments, and partnercollaborations.

How to Apply

Send your resume and a brief introduction outlining your relevantexperience and interest in the role to info@phridom.com.

We'd also love to see examples of simulation environments, roboticsprojects, synthetic data pipelines, or other work you're proud of.

About Us:

Phridom AI - Ability Robotics is an early-stage robotics and AIcompany building the core systems behind embodied intelligence. Ourtechnologies help robots understand the physical world, learn intelligentbehaviours, and operate reliably in real environments. We’re still in stealth,but we’re already working with a select group of partners to validate oursystems in high-impact robotics applications. If you're excited to buildfoundational technologies for the next generation of robotics and wantmeaningful ownership over hard technical problems, we'd love to hear from you.

Role Overview:

As a Robot Learning Engineer, you'll develop learning-based systemsthat enable robots to acquire and execute intelligent behaviors in the realworld. You'll work across data, perception, learning, and deployment, buildingpipelines that transform observations into robust robot actions. Your work willdirectly improve how embodied robots learn, adapt, and operate in real-worldenvironments, helping bridge the gap between machine learning research andreliable robotic systems.

What you'll work on

1.                         Design and implement learning-based pipelines that map perception anddata to robot behaviors

2.                         Train, evaluate, and iterate on robot learning systems usingreal-world or realistically collected data

3.                         Work with perception and systems engineers to define clean interfacesbetween learning components and upstream/downstream modules

4.                         Debug learning failures by analyzing data, model behavior, and systeminteractions

5.                         Support deployment of learned behaviors on real robotic platforms,considering stability, safety, and system constraints

6.                         Improve learning workflows to make experimentation, evaluation, anditeration more reliable over time

Technical Requirements

Must Have

1.                         Bachelor’s or Master’s degree in Robotics, Computer Science, MachineLearning, or a related technical field

2.                         3+ years of hands-on experience building learning-based systems for robotics or embodied agents

3.                         Practical experience with robotlearning methods, such as reinforcement learning, imitation learning, ordata-driven control

4.                         Experience training and evaluating models using real-world or noisy data, not only clean offline benchmarks

5.                         Solid understanding of how learning systems interact with perception,control, and system constraints

6.                         Strong programming skills in Python (and/or C++), with the ability tomaintain and iterate on non-trivial learning codebases

7.                         Ability to debug learning failures by reasoning across data, models,and system behavior

Nice to Have

1.                         Experience deploying learned behaviors on real robotic platforms

2.                         Familiarity with simulation-based training, sim-to-real transfer, orhybrid data pipelines

3.                         Experience working with experiment tracking, evaluation tooling, orreproducible learning workflows

4.                         Understanding of safety, stability, or latency considerations inrobot learning systems

5.                         Prior collaboration with perception, systems, or infrastructure teamsin a robotics setting

6.                         Good English proficiency (spoken and written)

Your Impact

1.                         Your work will enable robots to learn and perform increasinglycapable behaviors in real-world environments, not just controlled researchsettings.

2.                         You'll help transform data and perception into deployable robotintelligence by building learning systems that are robust, reliable, andscalable.

3.                         You'll improve how quickly the team can experiment, evaluate, anditerate on robot behaviors, accelerating the path from ideas to deployment.

4.                         You'll play a key role in bringing modern robot learning techniquesinto production systems that operate on real robotic platforms.

Why Join Us

Join us at an early stage and help build the core softwareinfrastructure behind humanoid and embodied robotic systems heading towardreal-world deployment. We move fast, ship often, and give engineers meaningfulownership—so you'll learn quickly, tackle high-impact challenges, and see yourwork running on real robots outside the lab. With active business across Chinaand beyond, you'll gain unique exposure to global robotics ecosystems,customers, and partners as the company scales.

Location

This role is based on-site in Singapore, working closely with theengineering team and robotic systems.

Occasional international travel to China and other regions may berequired for training, customer engagements, deployments, and partnercollaborations.

How to Apply

Send your resume and a brief introduction outlining your relevantexperience and interest in the role to info@phridom.com.

We'd also love to see examples of simulation environments, roboticsprojects, synthetic data pipelines, or other work you're proud of.

About Us:

Phridom AI - Ability Robotics is an early-stage robotics and AIcompany building the core systems behind embodied intelligence. Ourtechnologies help robots understand the physical world, learn intelligentbehaviours, and operate reliably in real environments. We’re still in stealth,but we’re already working with a select group of partners to validate oursystems in high-impact robotics applications. If you're excited to buildfoundational technologies for the next generation of robotics and wantmeaningful ownership over hard technical problems, we'd love to hear from you.

Role Overview:

As a Perception Engineer, you'll develop the vision systems thatenable robots to understand, track, and interact with the physical world inreal time. You'll work on object tracking, 3D reconstruction, state estimation,and interaction-aware perception, building algorithms that remain robust underocclusion, contact, and dynamic scene changes. Your work will directly improvehow embodied robots perceive and respond to their environments, enabling morecapable and reliable real-world deployments.

What you'll work on

1.                         Develop and deploy interaction-aware perception algorithms forrobotic systems, including object reconstruction, tracking, and stateestimation during interaction;

2.                         Design and implement high-performance 2D/3D tracking algorithms forstable perception in dynamic environments;

3.                         Develop 3D reconstruction and representation methods for interactionscenarios, including neural fields and explicit representations (e.g.,Gaussian-based, mesh-based), as well as 3D asset creation and scene generation;

4.                         Improve fine-grained object modeling and tracking in close-rangeinteraction scenarios, handling occlusion, contact, and rapid state changes;

5.                         Optimize model inference performance to meet real-time requirements(low latency, high throughput);

6.                         Deploy and integrate algorithms into robotic systems, resolvingreal-world performance and stability issues;

7.                         Collaborate cross-functionally to close the loop between data,models, and system performance;

8.                         Build evaluation pipelines to improve robustness and deployability.

Technical Requirements

Must Have

1.                         Bachelor's degree or above in Computer Science, Robotics, ElectricalEngineering, Automation, or a related field;

2.                          3+ years of experience incomputer vision or robotic perception, with experience in tracking, 3D vision,or interaction-related problems;

3.                          Strong fundamentals incomputer vision, including multi-view geometry, camera models, and 3Dreconstruction;

4.                          Experience with objecttracking methods (e.g., tracking-by-detection, multi-object tracking, 3Dtracking);

5.                          Proficiency in deep learningframeworks (e.g., PyTorch), with strong model development and optimizationskills;

6.                          Strong engineering skills,with experience deploying models on GPU or embedded platforms;

7.                          Strong debugging andproblem-solving skills in real-world systems.

Nice to Have

1.                         Experience in 3D reconstruction (e.g., SfM, SLAM, neural fields,Gaussian-based methods);

2.                          Experience with 3D objectdetection and tracking (e.g., multi-object or cross-view tracking);

3.                          Experience deployingalgorithms on real robotic systems (not limited to offline research);

4.                          Experience in modelacceleration and optimization (e.g., TensorRT, ONNX, quantization, pruning);

5.                          Experience with multi-sensorfusion (e.g., camera + depth or LiDAR);

6.                          Experience with large-scaledata processing or data pipelines;

7.                          Proficiency in English readingand writing, with the ability to understand technical literature.

Your Impact

1.                         Your perception systems will power real-world robotic deployments,helping robots understand objects, scenes, and interactions beyond controlledlaboratory settings.

2.                         You'll improve the reliability and robustness of robotic perceptionunder challenging conditions such as occlusion, motion, contact, andenvironmental uncertainty.

3.                         You'll help bridge cutting-edge 3D vision research and productionrobotics by deploying high-performance perception systems onto real roboticplatforms.

4.                         You'll play a key role in enabling next-generation embodied robots toperceive, track, and interact with the world more intelligently and reliably.

Why Join Us

Join us at an early stage and help build the core softwareinfrastructure behind humanoid and embodied robotic systems heading towardreal-world deployment. We move fast, ship often, and give engineers meaningfulownership—so you'll learn quickly, tackle high-impact challenges, and see yourwork running on real robots outside the lab. With active business across Chinaand beyond, you'll gain unique exposure to global robotics ecosystems,customers, and partners as the company scales.

Location

This role is based on-site in Singapore, working closely with theengineering team and robotic systems.

Occasional international travel to China and other regions may berequired for training, customer engagements, deployments, and partnercollaborations.

How to Apply

Send your resume and a brief introduction outlining your relevantexperience and interest in the role to info@phridom.com.

We'd also love to see examples of simulation environments, roboticsprojects, synthetic data pipelines, or other work you're proud of.

About Us:

Phridom AI - Ability Robotics is an early-stage robotics and AIcompany building the core systems behind embodied intelligence. Ourtechnologies help robots understand the physical world, learn intelligentbehaviours, and operate reliably in real environments. We’re still in stealth,but we’re already working with a select group of partners to validate oursystems in high-impact robotics applications. If you're excited to buildfoundational technologies for the next generation of robotics and wantmeaningful ownership over hard technical problems, we'd love to hear from you.

Role Overview:

As a Locomotion Engineer, you'll develop and deploy locomotionpolicies that enable humanoid and bipedal robots to move robustly in the realworld. You'll work across simulation and hardware, training policies, improvingsim-to-real transfer, and solving challenging problems in dynamics, control,and robot embodiment. Your work will directly power real-world robotdeployments and help advance the capabilities of next-generation humanoidsystems.

What you'll work on

1.                         Design, train, and evaluate locomotionpolicies in simulation (RL, imitation learning, etc.)

2.                         Develop and optimize Sim2Realpipelines, including domain randomization and system identification

3.                         Deploy locomotion policies onto real-worldbipedal/humanoid robots, ensuring robustness and stability

4.                         Enable generalization acrossmultiple robot embodiments (e.g., different biped morphologies)

5.                         Address real-world challenges such as contact uncertainty, sensornoise, latency, and actuator limits

6.                         Collaborate cross-functionally with hardware and software teams tobridge the sim-to-real gap

7.                         Analyze real-world failures and iterate on training and system design

Technical Requirements

Must Have

1.                         Bachelor’s degree or above in Robotics, Automation, ElectricalEngineering, Mechanical Engineering, or related fields.

2.                         3–6 years of experience in robotics system integration, automationimplementation, or related engineering roles.

3.                         Strong experience in roboticlocomotion or motion control, with hands-on policy training in simulation

4.                         Solid understanding and practical experience with Sim2Real transfer, including domainrandomization and/or system identification

5.                         Proven track record of deployinglocomotion policies onto real bipedal or humanoid robots (core requirement)

6.                         Strong foundation in dynamicsand control, especially for contact-rich systems

7.                         Experience with simulation tools such as MuJoCo, Isaac Gym/Sim, Newton, or similar

8.                         Proficiency in Python and modern ML frameworks (e.g., PyTorch, JAX)

Nice to Have

1.                         Experience deploying locomotion policies across multiple robot embodiments or platforms

2.                         Proven track record of multiplesuccessful Sim2Real deployments

3.                         Familiarity with whole-bodycontrol, state estimation, and low-level control systems

4.                         Direct experience with humanoidrobots

5.                         Experience with real-timesystems and high-frequency control loops

Your Impact

1.                         Your locomotion policies will run on real humanoid and bipedal robotsoperating outside controlled laboratory environments.

2.                         You'll help bridge the gap between simulation and reality, improvingrobustness against real-world challenges such as contact uncertainty, latency,sensor noise, and hardware variation.

3.                         You'll contribute to building more capable and adaptable robots byenabling locomotion across multiple embodiments and deployment scenarios.

4.                         You'll play a key role in turning cutting-edge research intoreliable, deployable robotic systems that can scale beyond prototypes anddemonstrations.

Why Join Us

Join us at an early stage and help build the core softwareinfrastructure behind humanoid and embodied robotic systems heading towardreal-world deployment. We move fast, ship often, and give engineers meaningfulownership—so you'll learn quickly, tackle high-impact challenges, and see yourwork running on real robots outside the lab. With active business across Chinaand beyond, you'll gain unique exposure to global robotics ecosystems,customers, and partners as the company scales.

Location

This role is based on-site in Singapore, working closely with theengineering team and robotic systems.

Occasional international travel to China and other regions may berequired for training, customer engagements, deployments, and partnercollaborations.

How to Apply

Send your resume and a brief introduction outlining your relevantexperience and interest in the role to info@phridom.com.

We'd also love to see examples of simulation environments, roboticsprojects, synthetic data pipelines, or other work you're proud of.

About Us:

Phridom AI - Ability Robotics is an early-stage robotics and AIcompany building the core systems behind embodied intelligence. Ourtechnologies help robots understand the physical world, learn intelligentbehaviours, and operate reliably in real environments. We’re still in stealth,but we’re already working with a select group of partners to validate oursystems in high-impact robotics applications. If you're excited to buildfoundational technologies for the next generation of robotics and wantmeaningful ownership over hard technical problems, we'd love to hear from you.

Role Overview:

As an Embodied AI Research Engineer, you'll develop the learningsystems that enable robots to understand, reason, and act in the physicalworld. You'll work at the intersection of Vision-Language-Action models,reinforcement learning, and real-world robotics, building end-to-endintelligence that translates perception into robust robot behavior. From modeldesign and training to deployment on physical robots, your work will directlyshape the capabilities of next-generation embodied AI systems operating in realenvironments.

What you'll work on

1.                         Develop and deploy intelligent algorithms for real-world roboticsystems, with a focus on Vision-Language-Action (VLA) models and reinforcementlearning (RL);

2.                          Design and implementend-to-end learning systems from perception to decision-making and control,improving generalization and task success rates in complex real-worldenvironments;

3.                          Lead or contribute to thetraining, evaluation, and deployment of VLA models in robotic applications,including data pipeline design, model architecture, and inference optimization;

4.                          Develop policy learningalgorithms using reinforcement learning (RL), imitation learning (IL), orrelated methods, ensuring stable execution on real robotic platforms;

5.                          Drive Sim-to-Real transfer,addressing challenges such as domain gaps, policy stability, and safety inreal-world deployment;

6.                          Collaborate closely withperception, simulation, and system engineering teams to close the loop betweendata, models, and system performance;

7.                          Build reproducible trainingand evaluation pipelines, and continuously improve robustness, stability, andefficiency in real-world deployments;

8.                          Stay up to date withstate-of-the-art research (e.g., VLA, Embodied AI, Foundation Models) andtranslate advances into practical robotic applications.

Technical Requirements

Must Have

1.                         PhD in Computer Science, Robotics, Artificial Intelligence, or arelated field;

2.                          Strong foundation in machinelearning and deep learning, with deep expertise in reinforcement learning (RL),imitation learning (IL), or related areas;

3.                          Experience inVision-Language-Action (VLA) or Embodied AI research or engineering;

4.                          Proficiency in at least onemajor deep learning framework (e.g., PyTorch or TensorFlow), with strongimplementation skills;

5.                          Familiarity with key roboticslearning challenges, such as policy learning, generalization, and Sim-to-Realtransfer;

6.                          Experience deployingalgorithms on real robotic systems, or a strong interest in bridging researchand production;

7.                          Strong problem decompositionskills and system-level thinking, with the ability to drive algorithmdeployment in complex systems;

8.                          Strong communication andcross-functional collaboration skills.

Nice to Have

1.                         Publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR,CVPR, CoRL, RSS);

2.                          Hands-on experience deployingalgorithms on real robotic platforms (e.g., manipulation or navigation);

3.                          Experience training oroptimizing large-scale models (e.g., foundation models or VLA models);

4.                          Experience deployingreinforcement learning in real-world systems (beyond simulation-only work);

5.                          Experience with large-scaledata pipelines, dataset construction, or automated labeling;

6.                          Experience with multimodallearning systems (vision-language-action);

Your Impact

1.                         You'll help define and deploy the intelligence stack behindnext-generation embodied robots, enabling them to perceive, reason, and act incomplex real-world environments.

2.                         Your work will bridge cutting-edge AI research and real-world roboticdeployment, transforming state-of-the-art models into reliable roboticcapabilities.

3.                         You'll advance the practical application of Vision-Language-Actionmodels, reinforcement learning, and foundation models in real robotic systems.

4.                         You'll play a key role in building scalable learning systems thatimprove robot generalization, adaptability, and autonomy across a wide range oftasks and environments.

Why Join Us

Join us at an early stage and help build the core softwareinfrastructure behind humanoid and embodied robotic systems heading towardreal-world deployment. We move fast, ship often, and give engineers meaningfulownership—so you'll learn quickly, tackle high-impact challenges, and see yourwork running on real robots outside the lab. With active business across Chinaand beyond, you'll gain unique exposure to global robotics ecosystems,customers, and partners as the company scales.

Location

This role is based on-site in Singapore, working closely with theengineering team and robotic systems.

Occasional international travel to China and other regions may berequired for training, customer engagements, deployments, and partnercollaborations.

How to Apply

Send your resume and a brief introduction outlining your relevantexperience and interest in the role to info@phridom.com.

We'd also love to see examples of simulation environments, roboticsprojects, synthetic data pipelines, or other work you're proud of.