Use simulation and digital twins to model production flows, equipment behavior, and system constraints, and to safely test and refine agent strategies before deployment.
Integrate predictive models (e.g. for demand, machine health, cycle time, yield) into expert systems to support proactive and prescriptive decisions.
Collaborate closely with process owners, planners, and equipment engineers to translate operational knowledge into rules, heuristics, and agent objectives.
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Work hands-on with ML engineers on detection models and risk scoring systems that are production-grade and auditable. Compliance analytics requires both explainability and reliability, and experience balancing those two requirements in practice will be important here.
Provide technical guidance and mentorship to data scientists and analytics engineers through code and methodology reviews, collaborative problem solving on complex compliance workstreams, and a consistent focus on raising the quality of the work across the team.
Partner with product managers on scoping, sequencing, and effort estimation for compliance analytics initiatives, bringing both technical and regulatory context to delivery planning conversations.
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Pioneer AI Safety: Partner with our AI Safety team to build highly secure, private, and robust systems. You will lead the charge in mitigating semantic drift, tracking confidence levels, and aligning agents with long-horizon tasks.
Set the Standard: Implement rigorous evaluation and benchmarking protocols to objectively measure, refine, and prove the effectiveness of our autonomous systems.
Proven Scale: 1 to 6+ years of experience in Software Engineering, Platform Engineering, or DevOps, with at least 3+ years strictly dedicated to MLOps, AI Infrastructure, or ML Engineering in a high-traffic, production environment. Candidates with no experience but with great interest in mastering advanced AI capabilities are welcome to apply.
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Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day.
As ByteDancers, we strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our Company, and our users. When we create and grow together, the possibilities are limitless. Join us.
Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.
NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Traffic-safety-and-data-analytics%29/32493-en_GB/
We regret that only shortlisted candidates will be notified.
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engagement with stakeholders through meetings and discussions.
Possess a PhD in Traffic Safety, Computer Engineering/Science, Data Science related subjects (incl. PhD to be received in 6 months after starting work).
Experience in developing driving simulator-based models.
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Develop and implement machine learning models (regression, classification, clustering) to predict maintenance needs and optimize operations.
Leverage Large Language Models (LLMs) to enhance data products through automated feature extraction, data enrichment, and intelligent information retrieval and decision making.
Create scalable data solutions that can handle real-time aircraft sensor data and maintenance logs.
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