Top Machine Learning Jobs in Singapore

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

Design, build, and manage large-scale search and content recommendation systems using machine learning and personalization techniques. Collaborate with content, product, and business teams to define success metrics, drive AI product improvements, and maximize content value and user impact.

Lead design and management of search and content recommendation services and models. Build personalized recommender systems using ML/AI, define success metrics with product and business teams, drive core module development, and translate PB-scale data insights into measurable product impact.

Design, develop, and maintain high-performance, secure Java backend services and APIs. Ensure reliability, scalability, and cost-efficiency across microservices, databases, messaging systems, and capacity planning. Troubleshoot, profile, benchmark, and optimize systems (including ML applications) and collaborate with Kazakhstan stakeholders.

Early-career Performance Engineer in the Binance Accelerator Program. Perform hands-on performance testing and tuning, design AI-powered test strategies using LLMs and ML, build AI-driven anomaly detection and bottleneck analysis tools, research new AI technologies, and improve reliability of large-scale distributed systems.

Design, back-test and implement pricing, risk management, and agency trading strategies; collaborate with developers to integrate models into the trading platform; participate in product ideation, modeling, parameter tuning, and risk evaluation.

The Solutions Advisor provides guidance to customers on supply chain management solutions, ensuring successful implementation and customer satisfaction through training and support.

Lead development and maintenance of the banks Data and AI risk management framework, set data risk appetite and controls, translate regulatory expectations, codify standards, and ensure consistent definition and reporting of data risks and control gaps across the Group.

Lead integration of AI into the chip development lifecycle: design and import AI tools/processes, localize and promote adoption, train engineers, monitor effectiveness, coordinate cross-functional teams, and continuously optimize AI-enabled workflows to improve R&D efficiency and competitiveness.

Structured graduate programme offering hands-on exposure to cloud, data, AI/ML, application development, automation, infrastructure and cybersecurity through client projects, mentorship, training, and industry certifications to launch technology careers.

As a Senior Impact Analyst, you will analyze sustainability challenges, design and manage interventions, and work closely with smallholder communities, emphasizing rigorous research and collaboration.

Technical co-founder (CTO) to define architecture, validate scientific hypotheses, build hands-on PoC/MVPs, lead the technical team, manage IP strategy, and communicate technology to investors and partners while scaling the product.

Lead and execute the regional data, analytics, and AI strategy while overseeing implementation, collaboration, team development, and governance compliance.

Design, develop, and debug complex software for semiconductor equipment; define specifications and test plans; lead projects; interact with customers for requirements and troubleshooting.

The role involves designing and developing tools in Python for trading and risk management, maintaining data pipelines, and collaborating with teams to enhance trading strategies using advanced techniques.

As a Senior AI Engineer, you will utilize AI engineering and delivery expertise to drive transformative projects for clients while building relationships and expanding your knowledge.

Lead and optimize III-V epitaxial growth processes primarily using MOCVD for semiconductor devices, supporting R&D and production with focus on yield improvement and process quality.

Lead and architect a low-latency, high-frequency cryptocurrency trading platform. Manage and mentor a distributed global engineering team, collaborate with traders and stakeholders, optimize network and systems performance, and build historical data and simulation systems to support trading strategies.

Develop and maintain internal systems and tools to automate production environments, build scalable web services, collect and visualize large data sets, support other technical teams, and implement innovations to improve trading infrastructure.

Join the Quantitative Trading desk to develop and deploy quantitative strategies, monitor trading and risk, implement signals and datasets in the execution platform, support the full trading cycle from risk calibration to execution, and communicate results and methodology to traders and senior management.

The Sales Manager will drive revenue and customer satisfaction through strategic client relationships, focusing on Microsoft Advertising solutions in the online media space.

A structured graduate programme delivering technical training, mentorship, certifications and hands-on client project experience across cloud, data, AI/ML, application development, automation, infrastructure and cybersecurity to prepare graduates for specialised technology career paths.

The HR Digital Specialist will lead digital transformation in HR by deploying AI and machine learning solutions, optimizing HR data management, and collaborating with stakeholders on analytics and technology improvements.

One-year, full-time fellowship supporting design, delivery, and evaluation of interventions for smallholder farmers. Duties include research and analysis, pilot design, field implementation, M&E, and cross-team collaboration with heavy mentorship and rotating in-country placements.

Lead design and implementation of an end-to-end AML risk management framework for overseas businesses: build KYB/CDD/EDD processes, risk-rating models, real-time suspicious transaction monitoring, STR/SAR reporting, and dynamic lifecycle risk controls while ensuring compliance with international AML regulations across jurisdictions.