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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 Assistant Principal Artificial Intelligence / Machine Learning Engineer to join our dynamic team. As a Assistant Principal Artificial Intelligence / 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 for our customers. Be Part of Our Success 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. 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. Stay up-to-date with the latest advancements: Keep abreast of the latest research and trends in software, machine learning and artificial intelligence. Evaluate and recommend new tools, libraries, and methodologies to enhance the efficiency and effectiveness of the machine learning workflow. Lead the team to design, develop, test and debug system software. Identify technical challenges and risks and develop solutions accordingly. Review code and architectural design. Drive standards in software design and development. Qualities We Value Strong programming skills in languages such as Python. Proficiency in machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn etc. Solid understanding of Statistical Analysis, Probability Theory, and Hypothesis Testing. Familiarity with machine learning tools on cloud platforms (e.g., AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark) is a plus. Experience: At least 5 years’ experience working in a similar role. Hands-on experience in designing, developing, and deploying machine learning models in real-world applications. Experience in full-stack development and strong knowledge of Software Engineering. At least 3 years hands-on experiences with Agile Development methodology. Experienced in at least 1 cycle of software development from design to development and testing. Knowledge of DevSecOps or practicing CI/CD for build and release automation. Strong programming skills and verifiable mastery of at least one of the following languages: Java, JavaScript, Python, C#, C++ Proficiency in Node.js, React, TypeScript, Spring Boot, Angular.js, Vue.js, Next.js, Express.js, FastAPI and other common frameworks to develop software for various platform. Proficiency in designing and maintaining scalable SQL/no-SQL databases such as MSSQL, MongoDB, PostgreSQL. Problem-solving and analytical mindset: Ability to analyze complex problems, break them down into solvable components, and develop innovative machine learning solutions. Strong mathematical and analytical skills are essential. Communication and collaboration: Excellent verbal and written communication skills, with the ability to convey technical concepts to both technical and non-technical stakeholders. Proven ability to work collaboratively in a team environment and effectively manage multiple priorities. Adaptability and continuous learning: Willingness to adapt to evolving technologies and learn new tools and techniques. Demonstrated commitment to staying updated with the latest advancements in machine learning and artificial intelligence. Resourceful, independent, responsive and conscientious. Role model and a mentor to every single member of the technical team. Good time management. 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 .
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.