770 Data Scientist Roles jobs in Singapore

At Atomionics, we build quantum gravimeters that are set to revolutionize the resource exploration industry. We are looking for a motivated intern with experience in time-series machine learning to contribute to the development of our high-performance sensors.

Responsibilities

• Design and implement a machine learning model to map time-series data from support sensors to our quantum gravimeter data.

• Evaluate model performance on both synthetic and experimental datasets.

• Work closely with our multidisciplinary team to validate results and address challenges such as limited data coverage or overfitting.

• Visualise the performance of the model as well as intermediate outputs.

Qualifications

• Education background physics, engineering, or data science is highly desirable.

• Hands on experience with neural networks applicable to time-series data

• Strong Python programming skills: NumPy, SciPy, pandas, visualization packages

• Proficient with ML libraries such as PyTorch/TensorFlow/Keras, etc.

• Familiar with signal processing basics: Fourier transform, windowing, filtering

• Analytical mindset

What can we offer you

• A chance to learn about the intricacies of deep tech research, product development, and strategy in a high-growth startup
• Work on the cutting edge of quantum technology
• A book allowance to help you grow and collectively build the Atomionics library
• Board games and curry night

We're looking for an experienced Machine Learning Engineer to design, build, and deploy scalable ML solutions while ensuring compliance with AI governance and responsible AI practices. It covers the full ML lifecycle from data pipelines and ML Operations deployment to model monitoring and stakeholder collaboration in a global banking environment.

Client Details

Our client is a globally established financial institution with a major technology hub in Asia. They play a critical role in supporting international banking operations through the development of in-house applications and enterprise-level digital initiatives. With strong regional integration and a forward-looking tech strategy, they continue to enhance operational efficiency and drive innovation across global markets.

Description

Key Responsibilities:

• Partner with data scientists and business teams to define ML solutions and develop Proof of Concepts.
• Deploy and manage ML models in production using ML Operations best practices (CI/CD, monitoring, versioning).
• Build and maintain scalable data pipelines while ensuring model performance and reliability.
• Ensure compliance with AI governance, responsible AI practices, and audit requirements.
• Support data exploration, feature engineering, and model development when required.
• Automate retraining, testing, and monitoring to sustain long-term model accuracy.
• Document ML workflows and collaborate with DevOps, IT, and security teams for enterprise integration.

Profile

A successful candidate should have:

• Have Master's degree in AI/ML or data science with proven model design and development expertise.
• At least 6 years' experience in data science and ML, including at least 3 years in ML engineering roles.
• Hands-on experience across the full ML lifecycle: data preparation, model development, deployment, and monitoring.
• Strong Python programming skills and familiarity with ML frameworks (scikit-learn, TensorFlow, PyTorch).
• Proficiency in NoSQL databases (Graph DB experience a plus) and use of ML Operations tools (MLflow, Airflow, Kubeflow, etc.).
• Experience with cloud platforms (AWS, GCP, Azure), CI/CD pipelines, and containerization (Docker, Kubernetes).
• Knowledge of responsible AI practices, governance, compliance, and techniques like NLP, time series, and supervised/unsupervised learning.
• Strong problem-solving, communication, and collaboration skills, with the ability to explain technical concepts to non-technical stakeholders in diverse environments.

Job Offer

Why this role?

• Opportunity to work on cutting-edge AI/ML projects within a global banking environment
• Exposure to enterprise-scale ML Operations practices and full ML lifecycle implementation
• Career growth through continuous learning and professional development
• Competitive compensation and attractive benefits package
• Collaborative and multicultural workplace culture

To apply online please click the 'Apply' button. For a confidential discussion about this role please contact Cheryl Sim (Lic No: R / EA No.: 18C9065) on Michael Page International Pte Limited, company number N (including Page Executive A) and Page Personnel Recruitment Pte Ltd (Registration Number: C)) operates under the EA Licence Numbers of 18S9099 and 18C9065.

Responsibilities:

• Collaborate with data scientists and business stakeholders to define ML solutions and develop Proof of Concepts (PoCs).
• Engineer and deploy ML models into production using MLOps best practices (model versioning, monitoring, CI/CD).
• Build and maintain scalable data pipelines and monitor model performance.
• Ensure models comply with organizational AI policies, responsible AI practices, and audit requirements.
• Support data exploration, feature engineering, and occasional model building.
• Automate model retraining, testing, and monitoring to maintain long-term performance.
• Document ML workflows, governance checkpoints, and risk assessments.
• Partner with DevOps, IT, and security teams to integrate solutions into enterprise platforms.

Requirements:

• Masters degree in AI, ML, or Data Science.
• 6+ years in data science/ML, with 3+ years in ML engineering.
• Experience across the end-to-end ML lifecycle: data wrangling, model development, deployment, and monitoring.
• Strong Python programming skills (pandas, scikit-learn, TensorFlow/PyTorch).
• Experience with NoSQL databases; Graph database experience desirable.
• Hands-on with MLOps tools (MLflow, TFX, Airflow, Kubeflow, etc.).
• Familiarity with cloud platforms (GCP, AWS, Azure) for ML deployment.
• Solid knowledge of data science techniques (supervised/unsupervised learning, NLP, time series).
• Experience with CI/CD pipelines and containerization (Docker, Kubernetes).
• Understanding of AI governance, model risk management, and regulatory requirements.
• Ability to communicate technical concepts to non-technical stakeholders.

Preferred:

• Experience with Responsible AI frameworks and bias/fairness testing.
• Exposure to feature stores, model registries, and data versioning.
• Knowledge of data privacy, anonymization, and compliance in regulated industries (e.g., banking, healthcare).

To apply, please visit and search for Job Reference: 9396Y33Y

To learn more about this opportunity, please contact Yingying at

We regret that only shortlisted candidates will be notified.

GMP Technologies (S) Pte Ltd | EA Licence: 11C3793 | EA Personnel: Lai Yingying | Registration No: R

This is in partnership with the Employment and Employability Institute Pte Ltd (e2i).

e2i is the empowering network for workers and employers seeking employment and employability solutions. e2i serves as a bridge between workers and employers, connecting with workers to offer job security through job-matching, career guidance and skills upgrading services, and partnering employers to address their manpower needs through recruitment, training, and job redesign solutions. e2i is a tripartite initiative of the National Trades Union Congress set up to support nation-wide manpower and skills upgrading initiatives.

By applying for this role, you consent to GMP Recruitment Services (S) Pte Ltds PDPA and e2is PDPA .

About Us

iCOMPASS Pte. Ltd. is a Singapore-headquartered RegTech company and spin-off from a leading advisory firm. iCOMPASS develops the world's first AI-powered compliance operating system designed for financial institutions. Designed in Singapore and built for global scalability, iCOMPASS is redefining how the financial industry approaches compliance in the age of AI.

Built at the intersection of regulatory expertise and cutting-edge technology, iCOMPASS transforms compliance from a reactive obligation into a proactive governance framework. With a vision to make regulatory compliance accessible, seamless, and adaptive, iCOMPASS empowers financial institutions of all sizes to reduce cost, mitigate risk, and enhance productivity.

Roles & Responsibilities

The successful candidate will design, build, and optimize LLM-driven solutions that support regulatory compliance, risk management. This role requires a deep understanding of both machine learning/NLP systems and compliance frameworks. The following summarises the scope of work:

• Model Development & Deployment

• Develop custom pipelines integrating structured (databases, transactions) and unstructured (news, documents, chat logs) data for compliance workflows.

• Implement explainability and interpretability layers to meet regulatory expectations.

• Compliance & Risk Applications

• Build systems that detect and classify financial crime risks (PEPs, RCAs, UBOs, sanctions exposure).

• Automate compliance document processing, regulatory reporting, and policy interpretation.

• Work closely with compliance officers to translate regulatory obligations into machine-executable rules.

• Systems Integration

• Deploy LLM-powered applications into enterprise-grade financial compliance platforms.

• Ensure robustness, scalability, and security of deployed models in production environments.

• Collaborate with engineering teams to integrate APIs, knowledge graphs, and third-party datasets.

• Research & Innovation

• Stay current with LLM advancements (RAG, fine-tuning, agents) and evaluate their applicability to compliance.

• Prototype tools for proactive risk detection and regulatory change monitoring.

• Others: Assist in ad-hoc projects or initiatives as assigned by management.

Requirements:

• Bachelor's Degree in Computer Science and any other relevant disciplines
• Strong analytical skills with the ability to assess risk and regulatory impact
• Ability to work independently and as part of a team in a fast-paced environment
• Excellent communication and presentation skills

Why Join Us?

• Engage in exciting projects to enhance compliance processes through innovation.
• Collaborative and dynamic work environment with opportunities for growth.
• We believe in rewarding impact and exceptional performance may be recognized with equity participation opportunities
• If you are looking to create impact in the regulated industry through technology transformation, this job is for you

If you are passionate about cross-pollinating regulatory compliance and technology, and enjoy problem-solving in a fast-paced environment, we invite you to apply for this role

Key Responsibilities

• Model Selection & Optimization: Identify, experiment with, and fine-tune state-of-the-art machine learning models for tasks such as video analytics, object recognition/detection, fraud detection, and multimodal generative AI.
• Deep Learning & LLMs: Work with transformer architectures, foundation models, and generative AI to develop and enhance multimodal AI solutions.
• Computer Vision: Develop and optimize models for real-time object detection, tracking, and recognition in video streams, ensuring performance in diverse conditions.
• Fraud Detection and other anomaly detection: Design and implement machine learning models for anomaly detection and fraud prevention using advanced statistical and AI techniques.
• Data Engineering & Processing: Preprocess large datasets, design efficient pipelines for real-time and batch processing, and integrate multimodal data sources (images, text, audio, video).
• Deployment & Scalability: Deploy models in production using cloud-based or edge computing solutions, ensuring performance, scalability, and cost-efficiency.
• Research & Innovation: Stay updated on the latest AI research, evaluate emerging models, and propose enhancements to improve performance and robustness.
• Collaboration & Integration: Work closely with software engineers, data scientists, and domain experts to integrate AI models into end-user applications.

Requirements

• Degree in Computer Science, AI, Machine Learning, or a related field.
• 4 to 5 years of relevant experience
• Strong experience in deep learning frameworks such as TensorFlow, PyTorch, or JAX.
• Proficiency in computer vision techniques, including object detection (YOLO, Faster R-CNN), video analytics, and multimodal learning.
• Hands-on experience with LLMs, transformers (GPT, BERT, T5, CLIP, etc.), and multimodal AI for text, image, and video synthesis.
• Experience in fraud detection and/or anomaly detection using machine learning, pattern recognition, and risk modeling.
• Experience in AWS SageMaker for model training and deployment preferred.
• Familiarity with MLOps and deployment on cloud platforms (AWS and/or GCP preferred) or edge devices.
• Strong problem-solving and analytical thinking abilities.
• Ability to work in a fast-paced, research-driven environment and adapt to evolving challenges.
• Excellent communication skills for presenting findings and collaborating across teams.
• Experience working with autonomous systems, robotics, or edge AI is a plus.

Interested parties, please click the "Apply Now" below AND apply via the GO portal.

We regret that only shortlisted applicants would be notified.

Toh Wen Qi, Celeste | REG No : R

PERSOLKELLY SINGAPORE PTE LTD | EA License No : 01C4394

By sending us your personal data and curriculum vitae (CV), you are deemed to consent to PERSOLKELLY Singapore Pte Ltd and its affiliates to collect, use and disclose your personal data for the purposes set out in the Privacy Policy available at You acknowledge that you have read, understood, and agree with the Privacy Policy.

We are seeking an experienced Machine Learning / AI Engineer to drive innovative digital initiatives across global projects. In this role, you will design, build, and deploy end-to-end machine learning solutions that are scalable, reliable, and compliant with AI governance and regulatory standards.

Key Responsibilities

• Collaborate with data scientists and business teams to define and implement ML solutions.
• Develop and deploy production-grade models using MLOps best practices (CI/CD, versioning, monitoring).
• Build and maintain data and model pipelines for scalability and performance.
• Ensure compliance with responsible AI, governance, and audit requirements.
• Automate retraining, testing, and monitoring of deployed models.
  Partner with DevOps, IT, and security teams for seamless integration.

Qualifications

• Master's degree in AI, ML, or Data Science.
• 6+ years in data science and ML, including 3+ in ML engineering.
• Proficiency in Python (pandas, scikit-learn, TensorFlow, PyTorch).
• Experience with MLOps tools (MLflow, Airflow, Kubeflow, etc.) and cloud platforms (AWS, Azure, GCP).
• Knowledge of CI/CD, Docker, Kubernetes, and NoSQL databases.
• Strong understanding of AI governance, model risk, and compliance.
  Excellent communication and problem-solving skills.

Preferred: Experience with Responsible AI, bias testing, feature stores, and data privacy in regulated sectors.

For a confidential discussion, please reach out to me at

Personal data collected will be used for recruitment purposes only.

Only shortlisted candidates will be notified / contacted.

EA Registration No: R

"Sanderson-iKas" is the brand name for iKas International (Asia) Pte Ltd, a company incorporated in Singapore under Company UEN No.: E with EA license number 16S8086.

Website:

TTS Specialist – Speech Model Training & Optimization

 
Location:
 Remote

 
Employment Type:
 Full-time

 
Department:
 AI & Engineering

About Us

At 

, we're redefining how people communicate through 
AI-driven voice technologies
. Our mission is to build the next generation of 
realistic, multilingual, and production-ready Text-to-Speech (TTS)
 systems that power conversations across phone, internet, and chat platforms.

We're looking for a 
TTS Specialist
 to join our core AI team. This is a 
high-impact, full-time role
 reporting directly to the 
CTO
, working alongside a talented international engineering team.

If you're passionate about building advanced TTS systems — from research to production — and want to shape the future of AI-powered communication, we'd love to meet you.

What You'll Do

• Design, train, and fine-tune TTS models
   for multiple languages, accents, and speaking styles.
• Improve 
  voice quality, pronunciation accuracy, prosody
  , and multilingual performance.
• Build and optimize 
  speech data pipelines
  , including audio preprocessing, alignment, phoneme conversion, and speaker adaptation.
• Implement and enhance 
  state-of-the-art TTS architectures
   (e.g., Tacotron 2, FastSpeech, VITS, StyleTTS2).
• Develop 
  real-time, production-ready inference pipelines
   for scalable deployment.
• Collaborate with linguists, localization teams, and backend engineers to scale voice coverage globally.
• Run 
  research experiments
   to push the limits of expressiveness, naturalness, and efficiency.
• Optimize models for 
  latency, cost, and robustness
   across diverse devices and environments.

What You'll Bring

• 3+ years of experience in 
  speech synthesis / TTS
   or related ML fields.
• Proven experience in 
  training and fine-tuning neural TTS models
   (e.g., Tacotron, FastSpeech, VITS, Glow-TTS).
• Strong proficiency in 
  Python
  , 
  PyTorch
   or TensorFlow.
• Hands-on experience with 
  audio data preprocessing
  , phoneme modeling, or linguistic features.
• Deep understanding of 
  signal processing
   and 
  speech representations
   (e.g., Mel-spectrograms, vocoders like HiFi-GAN, WaveGlow).
• Experience deploying TTS systems in 
  real-time or large-scale production
   environments.
• Familiarity with 
  multilingual TTS challenges
   (e.g., pronunciation modeling, code-switching, speaker adaptation).
• Experience with ML-Ops, GPU optimization, and cloud deployment.
• A strong research mindset and ability to stay current with 
  latest speech synthesis advancements
  .

Bonus Points:

• Experience with 
  voice cloning, speaker embeddings
  , or low-resource language modeling.
• Knowledge of 
  STT (speech-to-text)
   or conversational AI systems.
• Experience with containerized and serverless ML architectures (e.g., Docker, Kubernetes).
• Contributions to open-source TTS frameworks or publications in major speech conferences (e.g., Interspeech, ICASSP).

Why Join

• Work at the 
  cutting edge of speech AI
  , shaping the future of communication.
• Play a 
  core role in building production TTS systems
   for real-world applications.
• Fully remote team with a global mindset.
• Competitive compensation and growth opportunities.
• Inclusive, fast-moving culture that values innovation and impact.

Apply Now

If this sounds like you, send us your 
CV
 and a brief 
cover letter
 telling us why you're excited about joining 

.

Even if you don't meet 100% of the qualifications, we value diverse perspectives and encourage you to apply.

Let's build the 
next generation of AI voices
 together.

• Have Master's degree in the field of AI / ML and data science with proven ability to design and develop models

• 6+ years of experience in data science and machine learning, with at least 3+ years in ML engineering roles.

• Proven experience in end-to-end ML lifecycle: data wrangling, model development, deployment, and monitoring.

• Strong programming skills in Python (pandas, scikit-learn, TensorFlow/PyTorch, etc.).

• Strong knowledge in NoSQL databases (any experience in Graph database is desirable)

• Experience with MLOps tools: MLflow, TFX, Airflow, Kubeflow, or similar.

• Familiarity with cloud platforms (GCP, AWS, or Azure) for ML deployment.

• Knowledge of data science techniques including supervised/unsupervised learning, NLP, time series, etc.

• Experience with CI/CD pipelines and containerization (Docker, Kubernetes).

• Strong understanding of AI governance, model risk management, and regulatory requirements in AI.

• Ability to communicate technical concepts to non-technical stakeholders.