Job:

• Design and develop agentic AI systems for multi-step reasoning, tool usage, and workflow orchestration

• Build LLM-driven workflows and Python-based pipelines integrating agents with data, APIs, and engineering tools

• Develop and apply scientific machine learning models using experimental, sensor, and simulation data

• Create data pipelines for preprocessing, feature extraction, and integration of time-series and spatial data

• Deploy and operationalize AI/ML models and agents as scalable services or APIs

• Implement monitoring, evaluation, and validation for both agent systems and ML models

• Visualize data and model outputs to support analysis and decision-making

• Collaborate with domain experts to integrate AI into engineering and simulation workflows, and document reusable solutions

Requirement:

• Bachelor’s degree (minimum) in Mechanical Engineering, Computer Science, or a related engineering discipline

• 1–3 years of relevant work experience in AI, ML, software engineering, or applied research roles (industry, startup, or research labs)

• Strong proficiency in Python programming

• Hands-on experience building agentic AI systems that includes multi-step task execution, Tool/function calling and workflow orchestration across agents or components

- Practical experience with machine learning libraries, including NumPy, Pandas, SciPy, scikit-learn, TensorFlow and/or PyTorch

- Ability to independently design, build, and debug end-to-end AI workflows

• An agentic AI system that automates a complex multi-step task (engineering, data analysis, design, or simulation related)

o A GitHub, internal demo, or portfolio project demonstrating, agent orchestration, use of tools/APIs, non-trivial decision logic or reasoning loops

• Integration of LLM agents with data processing, visualization, or external software tools

The project does not need to be simulation-focused, but relevance to engineering workflows is a plus

• Experience with CFD or FEA workflows, particularly involving geometry, meshing, or simulation post-processing will be considered as an advantage

• Familiarity with open-source engineering tools such as OpenFOAM, SU2, CalculiX or similar will be considered as an advantage

• Effectiveness of agentic AI and SciML systems in real workflows

• Quality, scalability, and maintainability of deployed AI systems

• Demonstrated impact in reducing manual effort and improving engineering workflows

• Ability to translate ambiguous physical systems problems into structured AI/ML solutions

• Strong collaboration across AI, simulation, and experimental teams

All Successful candidates can expect a very competitive remuneration package and a comprehensive range of benefits.

Please email your resume in a detailed MS Word format to joyce@peopleprofilers.com stating

1) Current Drawn

2) Expecting Salary

3) Date Available

4) Reason to Leave each job:

We regret that only shortlisted candidates will be notified

Joyce Koh Ai Leng

People Profilers Pte Ltd

20 Cecil St, #08-09, PLUS Building, Singapore 049705

Tel: 6950 9737

www.peopleprofilers.com

EA License Number: 02C4944

EA Personnel Reg nos R1110618

Job ID:JOB-00551