144 Research Engineer jobs in Singapore

Hydroleap is a Singapore-based deep tech startup with a mission of disrupting the wastewater treatment industry. Our cutting-edge electrochemistry technology and innovative approaches to water and waste management have eliminated the need for manual interventions and toxic chemicals, making our solutions fully automated, cost-effective, and environmentally friendly—helping industries to be more water and energy efficient.

With multiple successful deployments across the Asia Pacific region, including in the agri-food, oil & gas, data center, desalination, and construction sectors, Hydroleap is significantly impacting how water and wastewater are treated.

As a company, we are proud to be backed by an impressive group of governmental and private venture capitalists, such as UntroD Capital, Mitsubishi Electric, Seeds Capital, State Government of Victoria, Wavemaker Partners, 500, SGInnovate, Sparklabs, and Entrepreneur First.

Join our team and be a part of a mission-driven organization that is changing the world, one drop of water at a time.

As Hydroleap is growing and offering solutions to more clients in new industry verticals, we are expanding our R&D team to expedite our product development and support Research & Development (R&D) projects in the field of electrochemical water treatment. We are seeking a research engineer with a background in chemical or environmental engineering to join our team.

The position will provide an opportunity for research engineers to apply their knowledge and experience in a fast-growing and innovative technology company.

• Work closely with R&D team and on a low-cost, chemical-free electrochemical water treatment process.
• Conduct lab-scale experiments and pilot-scale tests
• Perform analysis and measurement with instruments
• Interpret results and design new tests
• Provide and implement engineering solutions to process
• Engage R&D and product development activities to enable new product introduction and improvements
• Provide general assistance and organizational support to the R&D team
• Support site activities during commissioning and startup, including the commissioning of pilot systems

• MSc or BSc in Chemical or Environmental Engineering
• Research pilot experience
• Familiar and interested in water/wastewater treatment processes
• Familiar with water treatment processes and lab equipment
• Familiar and interested in scientific paper reading, research, and lab work
• Excellent analytical, problem-solving, troubleshooting, and project management skills
• Proficient in English; other language is an asset
• Proficient in Microsoft Office (Word, PowerPoint, Excel)
• Skilled in AutoCAD, SolidWorks, BioWin, WaterGEMS, or other related engineering software are a definite plus
• Commitment to the task assigned, self-initiative, and problem-solving skill

We thank all applicants for their interest; however, only those candidates selected for interviews will be contacted.

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

The Institute for Health Innovation & Technology (iHealthtech) at the National University of Singapore (NUS) was founded in 2017 to advance health through technological innovation. Focused on tackling clinical challenges, iHealthtech develops innovative health technologies, bridging the gap from the laboratory to the clinic and market. This process aims to ultimately benefit patients and society. To realise this mission, iHealthtech emphasises close interdisciplinary collaboration among its Principal Investigators, collaborators from engineering, medicine, and science, as well as industrial partners and entrepreneurs.

Job Description & Key Responsibilities

We have a hardware research engineer position opening at the Institute for Health Innovation & Technology, National University of Singapore (NUS) working on a wearable sensor development project. This project aims to develop a Wearable Sensor Network that integrates wireless, miniaturized sensors to measure physiological parameters across multiple body regions. This position provides an exciting opportunity to work on a highly multidisciplinary translational research and development project.

Key Responsibilities

We are looking for a passionate and self-motivated research engineer to join our team for the following key tasks
• Sensor Hardware Development: Design, prototype, and validate miniaturized, wireless sensors for physiological and biomechanical data collection.
• Embedded Systems: Develop firmware and optimize low-power microcontroller-based sensor platforms.
• Wireless Communication: Implement and optimize Bluetooth Low Energy (BLE) and other wireless protocols for real-time multi-sensor data transmission.
• PCB Design & Prototyping: Develop custom PCBs using tools like Altium, KiCad, or Eagle, ensuring compact, power-efficient designs.
• Signal Processing & Data Acquisition: Work on analog front-end (AFE) design for accurate signal acquisition and conditioning.
• Power Management: Develop low-power solutions for continuous, long-term wearable sensor operation.
• Testing & Validation: Conduct laboratory and field testing to assess sensor accuracy, reliability, and robustness in real-world conditions.
• Collaboration: Work closely with software engineers, data scientists, and domain experts to integrate sensor data into the real-time monitoring system.

• Bachelor’s or Master’s degree in Electrical Engineering, Biomedical Engineering, Embedded Systems, or a related field.
• 2+ years of experience in wearable sensor development, embedded systems, or IoT hardware design.
• Hands-on experience with sensor integration, PCB design, and low-power embedded systems.
• Proficiency in Bluetooth Low Energy (BLE) communication and embedded firmware development (e.g., C, C++, Python).
• Experience with microcontrollers (STM32, nRF52, ESP32, etc.) and real-time data acquisition.
• Knowledge of signal processing techniques for physiological data interpretation.
• Familiarity with power management strategies for wearable devices.Excellent writing and verbal communication skills

To apply, please send your cover letter, CV and names of 3 references (name, institution, email) to NUS Career Portal. Only shortlisted candidates will be contacted.

The Applied Research Engineer will play a pivotal role in advancing Tookitaki’s AI-driven compliance solutions by developing novel AI/ML algorithms and ensuring their practical implementation. This role bridges the gap between research and production , focusing on algorithm development, experimentation, and optimization to enhance Tookitaki’s capabilities in fraud detection, risk management, and anomaly detection . The role also involves collaborating with data scientists, engineers, and regulatory teams to create cutting-edge, regulatory-compliant AI solutions.

Key Responsibilities

1. AI/ML Model Research & Development

• Research, design, and implement state-of-the-art AI/ML models for fraud detection, risk assessment, and financial crime prevention.
• Optimize models for accuracy, efficiency, and scalability across various financial datasets.
• Experiment with graph-based AI, deep learning, and unsupervised learning techniques to improve detection capabilities.

2. Algorithm Optimization & Innovation

• Develop new feature engineering and model selection techniques to enhance AI model performance
• Optimize model inference speed for real-time and batch processing scenarios .
• Explore federated learning and privacy-preserving AI techniques to ensure data security and compliance. Data Analysis & Feature Engineering

3. Deployment & Engineering Collaboration

• Work closely with ML engineers and software developers to deploy AI models into production.
• Implement scalable AI pipelines that can handle large-scale financial data processing .
• Ensure AI solutions are explainable, interpretable, and aligned withregulatory requirements .

4. Data Analysis & Feature Engineering

• Analyze structured and unstructured financial datasets to extract meaningful features for ML models .
• Design and build robust data preprocessing pipelines to enhance model accuracy and generalization.
• Work with data engineering teams to ensure efficient and scalable data ingestion .

5. AI Ethics & Compliance

• Develop transparent and explainable AI models to meet financial industry compliance standards.
• Ensure AI models adhere to ethical AI guidelines, fairness, and bias mitigation strategies .
• Collaborate with legal and compliance teams to align AI research with evolving regulatory frameworks .

Qualifications and Skills

Education:

• Master’s or Ph.D. in Computer Science, Machine Learning, AI, Data Science, or related field .
• Strong research background in AI/ML, deep learning, or statistical modeling .

Experience:

• 5+ years of experience in applied AI research, machine learning, or data science .
• Proven track record in developing and deploying AI/ML models in real-world applications.
• Experience working with financial datasets, fraud detection, or regulatory compliance AI models (preferred).

Technical Expertise

• Strong programming skills in Python, TensorFlow, PyTorch, or JAX.
• Hands-on experience in NLP, anomaly detection, graph-based AI, and time-series analysis .
• Experience with big data processing frameworks (Spark, Hadoop) and cloud AI platforms (AWS/GCP).
• Expertise in model evaluation, hyperparameter tuning, and performance optimization .
• Knowledge of explainable AI (XAI), adversarial learning, and bias mitigation .

Soft Skills

• Strong problem-solving skills and the ability to translate complex research into practical applications .
• Excellent collaboration and communication skills to work with cross-functional teams.
• Ability to balance research innovation with real-world constraints and scalability .
• Strong analytical mindset with a passion for continuous learning and innovation .

Key Competencies:

1. AI/ML Research & Development : Ability to research, prototype, and implement cutting-edge AI models.
2. Algorithm Optimization : Expertise in fine-tuning models for real-world applications and performance improvements.
3. Scalability & Deployment : Hands-on experience in deploying ML models at scale .
4. Regulatory & Compliance Awareness : Understanding of AI ethics, explainability, and financial regulations .
5. Cross-Team Collaboration : Works closely

Success Metrics:

1. Successfully develop and deploy at least two AI models per year to enhance Tookitaki’s compliance solutions.
2. Improve model accuracy and efficiency by 20% through research-driven optimizations.
3. Ensure seamless deployment of AI models into production with 99.9% uptime .
4. Reduce false positives in financial fraud detection by 25% , improving risk assessment accuracy.
5. Publish at least one research paper or internal technical report annually on AI advancements.

Benefits:

• Competitive Salary : Aligned with industry standards and experience.
• Professional Development : Access to training in big data, cloud computing, and data integration tools.
• Comprehensive Benefits : Health insurance and flexible working options.
• Growth Opportunities : Career progression within Tookitaki’s rapidly expanding Services Delivery team.

Introducing Tookitaki

Tookitaki: The Trust Layer for Financial Services

Tookitaki is transforming financial services by building a robust trust layer that focuses on two crucial pillars: preventing fraud to build consumer trust and combating money laundering to secure institutional trust. Our trust layer leverages collaborative intelligence and a federated AI approach, delivering powerful, AI-driven solutions for real-time fraud detection and AML (Anti-Money Laundering) compliance.

How We Build Trust: Our Unique Value Propositions

1. AFC Ecosystem – Community-Driven Financial Crime Protection

The Anti-Financial Crime (AFC) Ecosystem is a community-driven platform that continuously updates financial crime patterns with real-time intelligence from industry experts. This enables our clients to stay ahead of the latest money laundering and fraud tactics. Leading digital banks and payment platforms rely on Tookitaki to protect them against evolving financial crime threats. By joining this ecosystem, institutions benefit from the collective intelligence of top industry players, ensuring robust protection.

2. FinCense – End-to-End Compliance Platform

Our FinCense platform is a comprehensive compliance solution that covers all aspects of AML and fraud prevention—from name screening and customer due diligence (CDD) to transaction monitoring and fraud detection. This ensures financial institutions not only meet regulatory requirements but also mitigate risks of non-compliance, providing the peace of mind they need as they scale.

Industry Recognition and Global Impact

Tookitaki’s innovative approach has been recognized by some of the leading financial entities in Asia. We have also earned accolades from key industry bodies such as FATF and received prestigious awards like the World Economic Forum Technology Pioneer, Forbes Asia 100 to Watch, and Chartis RiskTech100.

Serving some of the world’s most prominent banks and fintech companies, Tookitaki is continuously redefining the standards of financial crime detection and prevention, creating a safer and more trustworthy financial ecosystem for everyone.

• Learn and be receptive to new ideas and feedback
• Be courteous to colleagues and contribute to a positive and productive work environment
• Collaborate within the research department to formulate and meet goals as determined by the Director
• Attend regular virtual meetings
• Travel in person to meetings when necessary
• Investigate research questions around the IOTA protocol and the Tangle, using both mathematical models and software tools as applicable
• Understand and follow current trends in IOTA and DLT research
• Engage with the IOTA community, both online and in person
• Develop prototypes and maintain testnets and devnets
• Validate the IOTA protocol through simulations, prototypes, and collecting data from the various networks
• Work with engineers to develop the necessary software tools required for research
• Serve as an adviser on Engineering projects, ensuring theoretical soundness and providing oversight
• Interact with the IOTA community at meetups, community engagement events and conferences in a professional manner
• Be an evangelist for the IOTA mission through speeches, written communications, business development pitches, etc.
• Attend regular work progress meetings (to be mutually scheduled) as well as be available via email, chat forums or phone in case of urgent matters

Requirements:

• Masters' Degree in Computer Science or relevant
• Communication and writing skills: Be an evangelist for the IOTA mission through speeches, written
• communications, business development pitches, etc.
• Teamwork skills: Interact with the IOTA community at meetups, community engagements events and
• computer science, research, deep DLT understanding and knowledge, Go language, development of prototypes, cryptography

Please submit your updated resume in Word format by using the Apply Now Button.
We regret that only shortlisted candidates will be notified

Email resume to

People Profilers Pte Ltd, 20 Cecil Street, #08-09, PLUS Building, Singapore 049705.
Tel: 6950 9722

EA License Number: 02C4944
Registration Number: R111371
Posting Personnel: Tiffany Ong Meng Yen

Key Responsibilities

As an AI Research Engineer , you will explore the latest advancements in automated programming and generative game AI technologies, including but not limited to:

• AI Automated Programming (AP): Research and develop systems that allow AI to write, debug, and optimize game code autonomously.
• Procedural Game Mechanic Generation: Design AI models that can create game logic, gameplay rules, and level designs dynamically.
• LLM Code Generation & Optimization: Fine-tune large language models (such as GPT-4, LLaMA, DeepSeek) to generate high-quality code for engines like Unity, Cocos, and web-based platforms (H5).
• RAG for Code Reliability: Apply retrieval-augmented generation (RAG) techniques to improve the execution, stability, and maintainability of AI-generated code.
• AI NPCs & Game Interaction Systems: Develop intelligent game characters capable of adaptive behaviors, strategic decision-making, and personalized player interaction.
• Reinforcement Learning & Auto Debugging: Combine reinforcement learning (RLHF) with automatic code correction tools to enable self-healing AI code generation.

Requirements

We are looking for candidates who meet the following criteria:

• Master’s or PhD degree in Computer Science, Machine Learning, Natural Language Processing (NLP), Human-Computer Interaction (HCI), or Game AI.
• Strong familiarity with Large Language Models (LLMs) such as GPT-4, LLaMA, DeepSeek, and AI code generation tools like Code LLaMA, AlphaCode, or Codex.
• Proficiency in Python and machine learning frameworks (PyTorch, TensorFlow).
• Experience with game development programming languages (e.g. C++, C#, Unity, Unreal Engine, HTML5, or Cocos).
• Knowledge of Automated Programming (AP), RAG methods, AI-based debugging, and code optimization techniques.
• Track record of publications in top-tier AI conferences (e.g. NeurIPS, ICML, ICLR, ACL, AAAI, EMNLP) is a strong advantage.

Why Join Lobah Play?

• Innovate at the Frontier: Be part of the next wave of innovation in AI-generated games.
• Deep Tech Integration: Work at the intersection of LLMs and interactive entertainment.
• Collaborate with the Best: Join forces with global AI research teams and gain exposure to the latest advancements in generative AI and game technologies.

How to Apply

If you're passionate about AI, gaming, and redefining the future of interactive entertainment, we’d love to hear from you.

To apply, please send your CV and portfolio (if any) to with the subject line: (AI Research Engineer Application – Your Name)

Under the initial sponsorship of the Civil Aviation Authority of Singapore (CAAS), The MITRE Corporation, a U.S.-based, globally renowned research and development company, established its premier air traffic management research center in Singapore in 2015 to support the growth in the Asia Pacific Region. This research center, MITRE Asia Pacific Singapore (MAPS), needs a machine learning research engineer to be part of a dynamic team of multi-disciplinary professionals working to improve air traffic operations in Singapore and the Asia Pacific region. The role offers the opportunity to work on unique aviation datasets and complex operational challenges, collaborate with international experts, and contribute to aviation research with impact across the region.

The ideal candidate has a strong interest in applying machine learning to solve real-world problems in aviation, possesses excellent verbal and written technical communication skills, and strong analytical abilities.

A successful candidate will:

• Implement, train, and evaluate machine learning models under the mentorship of senior researchers and aviation subject-matter experts
• Perform data validation, data preprocessing, and feature engineering
• Conduct literature reviews and adapt deep learning architectures from research papers and emerging literature
• Analyze model performance using both traditional machine learning metrics and operationally relevant metrics
• Support reproducibility, experiment tracking, and model deployment efforts
• Contribute to technical reports and publications, and present findings to operational stakeholders

Required Skills and Experience:

• Bachelor's degree in Computer Science, Data Science, Electrical or Computer Engineering, Statistics, Mathematics, Physics, a related technical field, or equivalent experience
• 1–3 years of experience with Python and machine learning libraries (e.g., PyTorch, TensorFlow, scikit-learn)
• Deep knowledge of machine learning concepts
• Experience with GPU-accelerated training of deep learning models

Preference will be given to candidates who possess any of the following competencies or attributes:

• Master’s degree in a related technical field
• Exposure to applied research in academic or industrial settings
• Demonstrated experience working with real-world or multi-modal data (e.g., time series, geospatial, imagery)
• Familiarity with deep learning architectures such as CNNs, RNNs, transformers, or autoencoders
• Foundational knowledge of meteorology or air traffic management concepts
• Strong interest in aviation

MooVita is a high-tech startup specialised in providing autonomous driving solutions. The company is headquartered in Singapore with offices in Malaysia and China. MooVita is founded by a passionate team who are one of the first teams to put autonomous vehicles on Singapore public roads.

MooVita is developing a complete solution for last mile autonomous mobility and we are looking for a Researcher to perform in-depth research and algorithm development for intelligent autonomous driving behavior in dynamic and challenging on-road scenarios, leveraging on advanced contemporary methods in learning, prediction and planning under uncertainty.

Responsibilities:

• Research, develop, and translate methods at the frontier of learning, prediction, and planning to improve MooVita’s current behavior and decision-making stack
• Develop rigorous performance evaluation of developed intelligent behavior modules and benchmarking with existing best-in-class methods
• Work with team on efficient implementation, testing and validation of developed algorithms in AV simulation environments and on real vehicle

Requirements:

• Master or PhD degree in Computer Science, Engineering or related field
• Deep knowledge and practical experience with AI and learning based approaches (e.g. deep learning, reinforcement learning, transformer) for prediction, planning, or decision-making
• Excellent C/C++ and/or python programming skills
• Knowledge of Linux, and development on Linux systems
• Experience in development, application, or simulation of robotics and autonomous systems will be a plus

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

A Research Engineer position is open in the research group of A/P Wang Xinchao, at the Department of Electrical and Computer Engineering, National University of Singapore (NUS). The Research Engineer will work closely with the Principal Investigator (PI) on one or more research projects. The candidate will join the research team in the areas of Cyber Sentinel area.

The successful candidate is required to:

• Contribute to Cyber Sentinel, Dialogue, Speech Signal Processing and Machine Learning algorithms.
• Contribute to Image Processing and Machine Learning algorithms.
• Contribute to the implementation of Automatic Speech Recognition framework and development of systems.
• Contribute to the implementation of machine learning framework and development of image processing systems.
• To advance the knowledge, to publish in leading journals and conferences.
• To prepare and meet the project deliveries and milestones.

Qualifications / Requirements :

• Recognised degree in Bachelor / Master in Electrical Engineering, Computer Science or Computer Engineering
• Strong programming skills in one of the programming languages: C / C++, Matlab, Python
• Have prior project related experience
• Good team player and be able to work independently.
• Strong organizational, writing and interpersonal communications.
• Meticulous, able to work well under pressure and commitment to meet tight deadlines
• Open to fixed-term contract.

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Applications are invited from PhD students for a Research Engineer position in the Dr Prateek Bansal's research group at the National University of Singapore (NUS).

The project involves understanding micro-level residential and firm location choices in Singapore. The candidate will be responsible for:

(i) In-depth review of the literature, identifying factors affecting spatial location choices, review of the models of spatial location choice, and identifying appropriate factors and models for the case study.
(ii) Designing and conducting stated preference experiments
(iii) Developing and estimating discrete choice models for spatial location choice

The successful applicant is expected to pursue independent as well as collaborative research, must be willing participate in writing grant proposals and in the supervision of doctoral/postgraduate research students.

The candidate should
• Possess at least a bachelor’s degree in Travel behaviour, Management, Economics, Statistics, Psychology or related disciplines.
• Preferably be pursuing PhD in Travel behaviour, Management, Economics, Statistics, Psychology or related disciplines.
• Has good understanding of Classical and Bayesian econometric models of spatial location choice.
• Has strong background in developing stated preference surveys.
• Is proficient in programming econometric models in R, Python, or MATLAB.
• Good verbal and written communication skills.
• Open to fixed-term contract