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About ST Engineering ST Engineering is a global technology, defence, and engineering group with offices across Asia, Europe, the Middle East, and the U.S., serving customers in more than 100 countries. The Group uses technology and innovation to solve real-world problems and improve lives through its diverse portfolio of businesses across the aerospace, smart city, defence, and public security segments. Headquartered in Singapore, ST Engineering ranks among the largest companies listed on the Singapore Exchange. Our history spans more than 50 years, and our strategy is underpinned by our core values – Integrity, Value Creation, Courage, Commitment and Compassion. These 5 core values guide every aspect of our business and are embedded in our ST Engineering culture – from the people we hire, to working with each other, to our partners and customers. About our Line of Business – Mission Software & Services Our Mission Software & Services business provides leading-edge mission critical command, control, and communications (C3) systems with secured IT infrastructure and managed services. We support our client’s innovation journey through design thinking, analytics, and AI-enabled decision support with our full suite of cloud computing solutions. We provide intelligent, actionable insights and sustainable solutions to our valued partners in diverse industries including defence, government, and commercial sectors. Together, We Can Make A Significant Impact We are seeking an experienced Senior Data Scientist / Machine Learning Engineer to join our dynamic team. As a Senior Data Scientist / Machine Learning Engineer, you will play a key role in analyzing and presenting data, developing and implementing machine learning models and algorithms to solve complex business problems. Your expertise will contribute to enhancing the delivery service of analytics solutions and products to our customers. Be Part of Our Success Data analysis and insights: Perform exploratory data analysis, generate insights, and present findings to stakeholders. Use statistical methods and visualization techniques to communicate complex concepts and patterns effectively. Develop and deploy machine learning models: Design, build, and optimize machine learning models and algorithms to solve specific business problems. Collaborate with cross-functional teams to gather requirements, define objectives, and deploy models into production environments. Model training and evaluation: Train and fine-tune machine learning models using appropriate algorithms and techniques. Evaluate model performance and identify areas for improvement, employing techniques such as cross-validation, hyperparameter optimization, and ensemble methods. Model deployment and integration: Collaborate with software engineers and DevOps teams to deploy machine learning models into production environments. Implement APIs and integrate models with existing systems and applications to enable real-time decision-making. Performance monitoring and maintenance: Monitor model performance and address any issues or anomalies that arise. Continuously improve models by refining algorithms, optimizing code, and incorporating feedback from users and stakeholders. Stay up-to-date with the latest advancements: Keep abreast of the latest research and trends in machine learning and artificial intelligence. Evaluate and recommend new tools, libraries, and methodologies to enhance the efficiency and effectiveness of the machine learning workflow. Qualities We Value Shall have at least three (3) years of implementation and deployment experience in machine learning and statistical data analysis on large datasets. Shall have experience in translating business questions into analytical problems and using statistical techniques to derive actional insights using statistical software (Python, R, SAS), database languages (SQL), visualization tools (Qlik Sense), and deep learning framework (TensorFlow, PyTorch). Shall have the following skillsets: Data Wrangling, Data Visualization, DBMS, SQL, Python Preferably have completed at least one (1) project using Scrum or equivalent Agile development framework. Experience in these products/tools would be advantageous: MS Access (Front-end), SharePoint (Back-end), Power BI (Visualisation), Kubernetes, Docker/Podman, Microservices Architecture, DevSecOps Methodology Our Commitment That Goes Beyond the Norm An environment where you will be working on cutting-edge technologies and architecture. Safe space where diverse perspectives are valued, and everyone’s unique contributions are celebrated Meaningful work and projects that make a difference in people’s lives. A fun, passionate and collaborative workplace. Competitive remuneration and comprehensive benefits. Work location - based at either Changi , Tengah, Paya Lebar
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.