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Senior AI/ML Engineer

Pay
Pay not listed
Work setting
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Employment
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What you’ll work on

Full posting
  • Explore data, generate insights, and present findings to stakeholders

  • Design, build, and optimize machine learning models for business problems

  • Deploy models into production with software and DevOps teams

  • Implement APIs and integrate models with existing systems

  • Monitor model performance and fix issues or anomalies

From the employer’s posting
Perform exploratory data analysis, generate insights, and present findings to stakeholders
Design, build, and optimize machine learning models and algorithms to solve specific business problems
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
Monitor model performance and address any issues or anomalies that arise

What you’ll bring

All qualifications

Core experience

  • At least 3 years of ML implementation and deployment experience
  • Python, R, or SAS for statistical analysis
  • SQL and database skills
  • TensorFlow or PyTorch deep learning experience
  • Translating business questions into analytical problems
Qualification wording
at least three (3) years of implementation and deployment experience in machine learning and statistical data analysis on large datasets
using statistical software (Python, R, SAS)
Shall have the following skillsets: Data Wrangling, Data Visualization, DBMS, SQL, Python
deep learning framework (TensorFlow, PyTorch)
Shall have experience in translating business questions into analytical problems

About ST Engineering

Our Mission Software & Services business provides leading-edge mission critical command, control, and communications (C3) systems with secured IT infrastructure and managed services.

In the employer’s words · Read in context

Apply at ST Engineering

Posting record

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 5, 2026today
Recorded sightings
1

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How this job compares

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 6 and day 70.

From 4,442 similar postings that came down. Coming down is not always a hire.

ST Engineering is hiring

8 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • R
  • SAS
  • SQL
  • Docker
  • Kubernetes
  • Power BI
  • PyTorch
  • TensorFlow
Where the posting names them
- 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
- 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.
- 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

Your next step

Complete your application on careers.stengg.com. The employer’s form will show what is required.

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Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 625, the most 1,094, and the latest week had 876.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

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 AI/ML Engineer to join our dynamic team. 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.
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Singapore, SG

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