Top Machine Learning Jobs in Singapore

Develop AI-driven methods for skin and scalp biology discovery, integrating multimodal biological datasets to generate predictive insights. Build Design-Build-Test-Learn workflows, analyze imaging, omics, phenotypic, screening, and experimental data, and collaborate with experimental scientists to translate biological questions into computational models. Contribute to an AI-enabled discovery platform supporting autonomous and predictive scientific research.

Design, build, evaluate, and deploy AI systems for enterprise customers, taking solutions from use-case definition and architecture through production launch and scale. Develop prototypes, integrations, evaluation harnesses, and reusable tooling while resolving complex technical challenges involving reliability, latency, cost, safety, security, governance, and observability. Partner with customer and internal engineering teams to drive adoption, measurable business outcomes, and product improvements.

Drive APAC enterprise business development for custom AI solutions. Responsibilities include prospecting target accounts, building sales pipelines, leading consultative discovery, mapping business challenges to AI solutions, negotiating complex contracts, developing cloud and technology partnerships, and closing solution deals. The role also requires translating technical AI concepts into business value, advising customers on AI risks, influencing product roadmaps, supporting sales collateral, and contributing to pricing strategy and performance planning.

Designs and develops digital solutions using Microsoft Power Platform and Python. Maps cross-department processes, automates workflows, builds dashboards, maintains data quality, and develops analytics or machine learning prototypes. The role also integrates systems, supports data strategy, trains users, evaluates emerging technologies, and contributes to digital transformation initiatives.

Support customer implementations, onboarding, process improvement, internal tooling, knowledge-base management, operational reporting, and product QA. Translate customer feedback into scoped requirements while collaborating with Product, Engineering, and Customer Success teams. The intern will identify automation opportunities, track adoption and account health, maintain documentation, and help validate new releases in a fast-paced, fully onsite environment.

Develop and optimize generative AI and machine learning models, infrastructure, APIs, and integrations. Perform statistical analysis, data transformation, automation, model testing, audits, and evaluation for reliability, scalability, accuracy, and ethical compliance. Collaborate with technical and business stakeholders, communicate AI concepts clearly, research emerging techniques, and contribute to AI strategy and product capabilities.

Design, develop, and deploy software solutions for automated trading systems while collaborating with researchers on technology priorities.

Lead design and evaluation of cybersecurity architecture and controls for enterprise applications, specializing in blockchain and smart contract security. Provide technical guidance, perform threat modeling and security assessments, audit smart contracts, advocate secure SDLC practices, and recommend technology solutions.

Develop machine learning, statistical, optimization, computer vision, Generative AI, and Agentic AI solutions for smart manufacturing. Analyze operational data, build production-ready AI applications, support cloud deployment and model monitoring, and collaborate with manufacturing, engineering, supply chain, quality, IT, and software teams to improve quality, productivity, reliability, and decision-making.

Analytics Intern supporting AI and machine learning model development, quantitative risk analysis, data analytics, model testing, and evaluation of financial-services use cases. The role involves researching emerging techniques, analyzing complex datasets, validating models, and collaborating with quantitative analysts, risk managers, business teams, and technology stakeholders within Group Market Risk Management.

Lead AI/ML risk and control activities across APAC to strengthen governance, operational risk management, and regulatory compliance. Partner with business and control stakeholders to define controls, support testing and issue remediation, complete risk assessments, maintain control documentation, analyze metrics for emerging risks, and prepare materials for regulatory exams.

Join a front-office quantitative trading team to design and implement algorithmic execution strategies, back-test models and signals, build low-latency trading tools, and run real-time and post-trade transaction cost analysis to optimize execution.

Conduct threat hunting, security research, and intelligence analysis; build AI-powered threat research systems; analyze large datasets; validate AI-assisted findings and advise cross-functional teams to improve security posture.

Design and deploy real-time ML models and credit risk frameworks to detect fraud and assess merchant lending risk. Translate business needs into scalable analytics, monitoring, and decision-support tools. Partner with product, engineering, and operations to productionize models and improve risk visibility and decision quality.

Participate in semiconductor technology research and development projects: perform experiments, data analysis, modelling/simulation, and device characterization; generate technical reports, recommendations, and present findings. Leverage AI/ML and advanced analytics where applicable and collaborate with engineers to support process integration and next-generation memory technology development.

Summer internship applying data science, AI, software engineering, analytics, and automation to manufacturing and business problems. Interns analyze datasets, build dashboards/reports, develop automation or software solutions, and present findings to improve operational efficiency and support digital transformation.

Lead the roadmap, discovery, delivery, adoption, quality, and continuous improvement of internal AI platforms. Translate business needs into priorities, requirements, pilots, releases, and measurable outcomes. Partner with engineering, product owners, security, legal, and business teams on reliability, costs, responsible AI, data handling, and user adoption. Mentor product colleagues and influence stakeholders without direct authority.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Develop machine learning models and agentic AI prototypes for semiconductor yield, reliability, testing, and manufacturing analytics. Prepare and transform high-volume engineering data, build feature-engineering pipelines, evaluate models, and explore workflow automation using engineering and enterprise tools. Deliver technical documentation, demonstrations, and presentations while collaborating with Product Engineers and AI mentors.

Develop and deploy applied AI/ML solutions for intelligent transportation, including computer vision, generative AI, agentic AI, data pipelines, and machine learning algorithms. Collaborate with technical and business stakeholders, iteratively refine products with users, evaluate emerging technologies, and establish engineering best practices. The role also involves cloud solution deployment, DevOps practices, testing, version control, and knowledge sharing.

Conduct ML/AI research to extract patterns from diverse datasets (including unstructured data), implement algorithms in high-quality code, back-test models, and document findings for quantitative trading applications.

PhD internship conducting research applying statistics, machine learning and AI (e.g., deep learning, NLP) to market data. Implement and test algorithms in production-quality code, work with large and unstructured datasets, back-test models, and document findings while collaborating with senior researchers.

As a Software Engineer Intern, you'll develop high-performance platforms and technological tools for trading strategies while collaborating with senior team members at Citadel Securities.

Software Engineers are matched confidentially with Dragonfly portfolio companies hiring across crypto and blockchain. Roles may span backend, frontend, full-stack, mobile, infrastructure, data, security, machine learning, and DevOps. Candidates should have software engineering experience and an interest in crypto, blockchain, or open-source technologies. Startup or crypto-native project experience is preferred. Opportunities may be remote, hybrid, or in-person worldwide.

Build and operate production-grade AI data pipelines and financial knowledge services for equities content. Responsibilities include processing text, tables, documents, and multimedia; creating knowledge bases and search indexes; engineering RAG retrieval and citation systems; integrating LLMs and NLP models; managing orchestration, APIs, quality, cost, observability, reliability, and scalable production operations.