Assistant/ Principal Machine Learning Engineer, Jurong East

Location Group Engineering Centre, ST Engineering Jurong East Hub (Singapore)
About the Role We are seeking an exceptional
Assistant/
Principal Machine Learning Engineer
to lead the delivery of
high‑impact, production‑grade AI solutions
across multiple business domains within
ST Engineering . Based within the
Group Engineering Centre (GEC) – Video Analytics team , this role plays a critical part in enabling and accelerating advanced video analytics capabilities across all ST Engineering businesses. You will operate at both a
hands‑on technical
and
technical leadership
level, tackling complex real‑world problems by applying
Computer Vision, Machine Learning, and Large / Vision‑Language Models (LLMs / VLMs)
in innovative ways. In addition to technical delivery, you will help
shape technical direction ,
mentor engineers , and influence best practices across projects and teams. This role is ideal for a seasoned engineer who enjoys working on
challenging, cross‑domain problems , thrives in a collaborative environment, and is motivated by seeing AI solutions deployed at scale.
Key Responsibilities Technical Leadership & Delivery Lead the
design, development, and deployment
of advanced video analytics and AI systems across diverse domains such as smart cities, transport, defence, security, and industrial solutions. Architect
reusable,
scalable, robust, and maintainable
machine learning and computer vision solutions suitable for enterprise and mission‑critical environments. Drive the adoption of
state‑of‑the‑art ML, CV, and foundation models , including LLMs and VLMs, to solve complex video understanding problems. Translate ambiguous business and operational requirements into
clear technical strategies and implementable solutions . Provide technical oversight across multiple projects, ensuring engineering quality, performance, and reliability.
Innovation & Applied Research Explore and apply emerging research in
computer vision, multimodal learning, self‑supervised learning, and generative AI
to real‑world video analytics use cases. Prototype and evaluate novel approaches involving
LLMs/VLMs
for tasks such as video reasoning, summarisation, event understanding, and human‑AI interaction. Balance innovation with pragmatism, ensuring solutions are
deployable, supportable, and cost‑effective .
Team Leadership & Mentorship Act as a
technical mentor and role model
to machine learning and software engineers within the Video Analytics team. Provide guidance on system design, model development, experimentation, and MLOps best practices. Support the growth of engineering capability across GEC by sharing knowledge and establishing reusable frameworks, tools, and patterns. Contribute to technical reviews, hiring activities, and capability planning as a senior member of the engineering community.
Stakeholder Collaboration Work closely with business units, product owners, domain experts, and system integrators across ST Engineering. Clearly communicate technical concepts, trade‑offs, and risks to both technical and non‑technical stakeholders. Support pre‑sales, feasibility studies, and solution consultations where deep technical expertise is required.
Required Skills & Experience Essential Extensive experience (typically 4+ years) in
Machine Learning and/or Computer Vision , with a strong track record of delivering solutions to production. Deep expertise in
computer vision
techniques (e.g. detection, tracking, segmentation, action recognition, video understanding). Strong practical experience with
deep learning frameworks
such as PyTorch or TensorFlow. Proven experience designing and deploying
end‑to‑end ML systems , including training, evaluation, optimisation, and deployment. Hands‑on experience leveraging
LLMs and/or Vision‑Language Models
as part of applied AI solutions. Strong software engineering fundamentals, including Python, system design, and version control. Experience working in complex, multi‑stakeholder or multi‑domain environments. Desirable Experience with
MLOps , model lifecycle management, and production monitoring. Familiarity with edge AI or resource‑constrained deployment scenarios. Exposure to cloud platforms, containerisation, or distributed systems. Experience leading or mentoring engineers in a technical capacity. Ability to apply
audio analysis and audio‑visual learning
techniques, such as sound event detection, speech‑related analysis, or audio‑visual fusion, as part of broader analytics solutions is a plus. Advanced degree (MSc or PhD) in Computer Science, Engineering, AI, or a related field.
What We Offer The opportunity to work on
challenging, real‑world AI problems
with meaningful impact across multiple industries. A senior technical role within a
group‑level engineering team
influencing solutions across the entire ST Engineering ecosystem. Access to complex datasets, real operational environments, and the ability to take solutions from concept to deployment. A collaborative environment that values
technical excellence, continuous learning, and innovation .
If you are passionate about advancing
video analytics through cutting‑edge machine learning , and enjoy combining deep technical work with leadership and mentorship, we would welcome your application.