Total 8 structural engineer job vacancies

About the Role
We are looking for a Junior to Mid-Level ML Engineer to join the Model Engineering team. This role is suited for someone who enjoys working hands-on with computer vision models and understands models as systems to be trained, evaluated, improved, and optimised. You will work across the model lifecycle, including dataset preparation, architecture development, model training, evaluation, performance analysis, and optimisation for real-world computer vision applications.

Responsibilities

• Train, fine-tune, and evaluate computer vision models for classification, object detection, segmentation, pose estimation, and action recognition.
• Improve model performance through architecture enhancements, custom heads, backbone modifications, loss functions, and training strategy optimisation.
• Design experiments, conduct ablation studies, benchmark new techniques, and analyse model trade-offs.
• Investigate edge cases, debug failure cases, and improve model accuracy, robustness, and efficiency.
• Optimise models based on practical constraints such as latency, throughput, resource usage, and hardware limitations.
• Collaborate with engineering teams to improve dataset quality, model performance, and system reliability.

Requirements

• Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field.
• At least 2 years of hands-on experience training, fine-tuning, and evaluating computer vision models.
• Strong hands-on experience with PyTorch and/or TensorFlow.
• Proficiency in Python and familiarity with Linux environments and command-line tools.
• Experience with computer vision tasks such as classification, object detection, segmentation, pose estimation, or action recognition.
• Experience modifying models beyond configuration-level changes, including architectures, backbones, heads, loss functions, or training pipelines.
• Experience designing experiments, conducting ablation studies, analysing model performance, and debugging failure cases.
• Familiarity with multimodal, vision-language, foundation, or open-vocabulary models.
• Experience with model optimisation techniques such as quantisation, pruning, or distillation.
• Familiarity with experiment tracking, reproducibility, and structured machine learning workflows.

We are looking for an Engineering Manager / Lead Software Engineer to take on complex and meaningful technical challenges in the public sector, driving digital transformation that directly improves lives at scale.

In this role, you will be responsible for setting technical direction, shaping engineering processes, and ensuring delivery of one or more products owned by your team. You will also play a key role in building an engineering culture that values excellence, collaboration, and long-term impact.

Job Responsibilities:

• Defining your team’s engineering vision, strategy, and roadmap in alignment with broader organizational goals.
• Staying on top of industry trends, with strong knowledge of how systems should be architected, engineered, and maintained at scale.
• Designing and guiding the implementation of systems across SaaS solutions, leveraging cloud technologies where appropriate.
• Partnering with stakeholders to prioritize and manage product roadmaps, ensuring incremental and effective delivery towards long-term vision.
• Creating and maintaining a technical plan that anticipates future product and infrastructure needs.
• Coaching and mentoring engineers through regular feedback, supporting professional growth and career development.
• Driving adoption of best practices in quality, reliability, performance, and security within your teams.
• Encouraging strong engineering culture and introducing tools/processes that maximize effectiveness and impact.
• Actively identifying and initiating high-value engineering initiatives that contribute to the public good.
• Contributing to recruitment, particularly for senior technical roles.

Job Requirements:

• Proven experience building and operating large, high-availability software systems at scale.
• At least 10 years of development experience, with 5+ years coaching and mentoring engineering teams of 5+ people.
• Experience with modern full-stack application development, spanning contemporary front-end frameworks and scalable backend services across multiple programming languages.
• Hands-on technical expertise across the technology stack, including infrastructure, client-side, backend services, APIs, databases, performance, and data.
• Strong background in end-to-end system development, from user interfaces through backend and integration layers.
• Familiarity with Agile development, modular design, automation, TDD, CI/CD pipelines, pair programming, and infrastructure automation.
• Exposure to cloud platforms (e.g. AWS, Azure) and container technologies (e.g. Docker, Kubernetes).
• Excellent understanding of engineering leadership, balancing technical expertise with the soft skills needed to inspire and guide teams.
• Passion for engineering craftsmanship, teamwork, and creating meaningful impact through technology.
• Strong ability to lead teams toward achieving ambitious goals together.

Our client is a fast-growing AI company building enterprise-grade agentic automation solutions for large organizations. They are looking for a hands-on, client-facing AI engineer to work directly with enterprise clients and bring AI-driven automation workflows into production.

This role is best suited for a strong engineer who enjoys solving ambiguous customer problems, working close to real business operations, and moving from discovery to implementation quickly. You will help clients identify where AI agents can create practical impact, then design, build, integrate, deploy, and iterate solutions within complex enterprise environments.

You will work across backend engineering, solution design, integrations, data flows, deployment, and customer engagement, with a strong focus on reliability, business value, and production outcomes.

Key Responsibilities

• Partner directly with enterprise customers to understand their workflows, pain points, technical environments, and success criteria.
• Translate ambiguous business problems into clear technical plans, solution designs, and production-ready implementations.
• Build, configure, and deploy AI agents and automation workflows that connect with customer systems, data sources, APIs, and business processes.
• Own the delivery lifecycle from discovery and scoping through build, testing, launch, monitoring, and ongoing iteration.
• Write high-quality code for backend logic, integrations, workflow automation, data handling, and deployment requirements.
• Work with real customer data and production environments to test performance, measure outcomes, and improve solution effectiveness.
• Collaborate with product and engineering teams to improve the platform based on customer needs, deployment learnings, and field feedback.
• Run technical workshops, guide customers through implementation decisions, and explain technical trade-offs clearly to both technical and non-technical stakeholders.
• Identify repeatable patterns, create documentation, improve internal tools, and help scale delivery practices as the team grows.
• Take ownership of reliability, performance, maintainability, and long-term customer success after deployment.

Requirements

• Minimum 6 years of experience in software engineering, AI engineering, implementation engineering, technical consulting, or similar hands-on technical roles.
• Strong backend engineering fundamentals, including system design, APIs, integrations, data flows, and production systems.
• Experience with AI agents, LLM applications, automation platforms, workflow tools, or data-heavy enterprise systems.
• Experience building or deploying AI solutions in complex customer environments, especially where requirements are ambiguous or evolving.
• Comfort working directly with enterprise customers, including business, operations, IT, and technical stakeholders.
• Ability to quickly understand customer workflows and identify where automation or AI can deliver practical business impact.
• Strong ownership mindset, with the ability to create clarity, drive decisions, and move projects forward independently.
• Clear communication skills, with the ability to explain technical concepts, implementation plans, risks, and trade-offs in a practical way.
• Experience working with production systems, including testing, debugging, monitoring, performance improvement, and ongoing iteration.
• Regular use of AI tools and a practical understanding of what current AI technologies can and cannot do.
• Comfort operating in a fast-moving, early-stage environment where priorities may shift and solutions need to be developed quickly but thoughtfully.

Nice to have

• Experience in enterprise implementation, deployment, professional services, customer engineering, or technical consulting.
• Experience working with large enterprise clients in Singapore, especially across FSI, telco, insurance, aviation, or other complex industries.
• Startup or zero-to-one environment experience.

Dear Applicant,

If you or someone you know isinterested, please send the CV directly to VeronicaE@evolutionjobs.sg (mostpreferred, as I may overlook some CVs due to the high volume).

Please note that visasponsorship is not available at this time.

JD

AI Solutions Engineer – 1-Year Renewable Contract
Industry: Insurance
Location: Singapore
Contract: 1-year renewable

We are looking for an AI Solutions Engineer tosupport AI/GenAI initiatives within the insurance domain. The ideal candidateshould have strong hands-on experience in AWS / Azure, with the abilityto design, build, and deploy AI solutions in an enterprise environment.

Key Responsibilities:

Design, develop, and implement AI/GenAI solutions using Amazonand Microsoft.

Work with business and technology stakeholders to understandrequirements and translate them into scalable AI solutions.

Build and integrate AI models, APIs, workflows, andautomation tools into existing systems.

Support proof-of-concepts, solution design, testing,deployment, and production readiness.

Collaborate with data, cloud, security, and applicationteams to ensure solutions meet enterprise standards.

Provide technical guidance on AI architecture, cloudintegration, and best practices.

Requirements:

Strong experience as an AI Engineer / AI SolutionsEngineer / Cloud AI Engineer / Machine Learning Engineer.

Must have hands-on experience with AWS/Azure

Good understanding of GenAI, LLMs, prompt engineering, RAG,model integration, and AI solution deployment.

Experience with Python, APIs, cloud-native architecture, andenterprise application integration.

Insurance or financial services experience is highlypreferred.

Strong communication skills and ability to work with bothtechnical and business stakeholders.

Key Responsibilities

• Develop, enhance, and maintain key features across a SaaS platform using React, TypeScript, and Node.js.
• Build, document, and maintain RESTful APIs that support frontend and product functionality.
• Work closely with product, design, and engineering teams to shape and deliver user-facing features.
• Write high-quality, scalable, maintainable, and testable code.
• Participate in code reviews, technical discussions, and architecture planning.
• Contribute to DevOps practices, CI/CD workflows, and infrastructure-related decisions.
• Take ownership of technical delivery and support the adoption of strong engineering standards as the team grows.
• Be hands-on across the full stack initially, with the opportunity to gradually move into a technical leadership role.
• Support future team expansion by providing technical guidance, mentoring engineers, and improving development processes.
• Work effectively in a fast-moving, iterative environment where ownership, pragmatism, and adaptability are important.

Requirements

• Proven experience in software engineering or full-stack development.
• Strong hands-on experience with React and TypeScript.
• Solid backend development experience using Node.js.
• Good understanding of RESTful API design and development principles.
• Familiarity with relational databases, ideally PostgreSQL.
• Experience using Git and working with CI/CD pipelines.
• Strong communication skills and a collaborative working style.
• Prior experience mentoring engineers, leading a small technical team, or owning technical delivery would be advantageous.
• Comfortable remaining hands-on while gradually taking on more technical leadership responsibilities as the engineering team scales.
• Prior experience in a startup, scale-up, early-stage product company, or entrepreneurial environment is strongly preferred.

Strong Plus:

• Experience with pair programming.
• Experience practicing test-driven development/TDD.
• Familiarity with Kanban or other lean, iterative delivery methods.
• Exposure to AWS, DevOps, testing frameworks, performance tuning, or infrastructure-related work.

Responsibilities

• Serve as the primary technical point of contact for customers using Silicon Photnics (SiPh) test solutions.
• Provide post-sales technical support, including installation, ramp up, optimization, troubleshooting, and ongoing customer support.
• Work closely with customer engineering and test teams to ensure successful deployment and operation in R&D, NPI, and manufacturing environments.
• Support technical discussions, evaluations, demonstrations, and solution recommendations during the pre-sales process.
• Collaborate with internal sales, applications, service, and engineering teams to resolve technical issues and deliver customer success.

Requirements

• Bachelor's Degree in Electrical Engineering, Photonics, Physics, Semiconductor Engineering, or a related discipline.
• 3+ years of experience in Solutions Engineering, Applications Engineering, Test Engineering, or related semiconductor roles.
• Handson experience with Silicon Photonics (SiPh), optical test solutions, or photonics-based technologies.
• Strong understanding of optical and electrical testing, test automation, and system integration.
• Customer facing experience with strong troubleshooting, communication, and stakeholder management skills.
• Experience supporting semiconductor customers, including foundries, IDMs, or OSATs, is preferred

Key Responsibilities

Cloud Infrastructure & Automation

• Design, deploy, and maintain cloud environments on AWS or GCP.
• Develop and manage infrastructure using Infrastructure-as-Code tools such as Terraform or similar technologies.
• Implement secure networking architectures, including VPCs, private connectivity, VPNs, peering, and network segmentation.
• Establish scalable multi-environment and multi-account cloud strategies.

Container Platform & Kubernetes

• Build and manage Kubernetes environments for production workloads.
• Configure cluster security, RBAC, autoscaling, workload isolation, and governance controls.
• Create standardized deployment frameworks for microservices, backend services, and AI-related workloads.
• Support both real-time and batch processing environments.

CI/CD & Release Automation

• Design and optimize CI/CD pipelines to streamline software delivery.
• Implement automated testing, deployment validation, and release management processes.
• Support deployment strategies such as blue-green, canary, and phased rollouts.
• Improve developer productivity through automation and deployment standardization.

Observability & Site Reliability

• Implement monitoring, logging, tracing, and alerting solutions.
• Define service reliability metrics, performance objectives, and operational standards.
• Support incident response processes, root-cause analysis, and continuous service improvement.
• Develop operational runbooks and support on-call readiness.

Security & DevSecOps

• Strengthen cloud security through identity and access management best practices.
• Manage secrets, certificates, and sensitive configuration securely.
• Implement vulnerability scanning, dependency analysis, and container security controls.
• Enforce security policies through automation and governance frameworks.
• Support audit readiness and compliance requirements.

AI/ML Platform Support

• Collaborate with data science and machine learning teams to operationalize AI solutions.
• Support model deployment, inference services, batch processing, and ML infrastructure.
• Monitor performance, availability, and resource consumption of AI workloads.
• Contribute to platform capabilities that improve AI product scalability.

Cost Optimization

• Monitor cloud spending and resource utilization.
• Implement tagging, budgeting, and optimization initiatives.
• Drive efficiency improvements without compromising performance or reliability.

Developer Experience

• Build self-service infrastructure capabilities and reusable engineering templates.
• Improve internal tooling and automation workflows.
• Maintain clear technical documentation and operational guidelines.
• Help create a smooth developer experience across engineering teams.

Requirements

Essential Skills & Experience

• Minimum 4 years of experience in DevOps, Site Reliability Engineering, Platform Engineering, or related infrastructure roles.
• Strong hands-on experience with AWS or Google Cloud Platform.
• Proven expertise with Infrastructure-as-Code tools, preferably Terraform.
• Solid Kubernetes administration and containerization experience (Docker, Helm, Kustomize, etc.).
• Strong knowledge of CI/CD pipelines and modern software delivery practices.
• Good understanding of Linux systems, networking, and automation scripting using Python and/or Bash.
• Experience implementing monitoring, logging, and observability solutions.
• Strong understanding of cloud security principles, IAM, secrets management, and infrastructure hardening.
• Ability to collaborate effectively with software engineers, product stakeholders, and technical leadership.
• Strong documentation and communication skills.

Preferred Qualifications

• Experience with GitOps practices and tools such as ArgoCD or Flux.
• Exposure to policy-as-code and infrastructure testing frameworks.
• Familiarity with data engineering or machine learning ecosystems.
• Experience working with distributed systems, streaming platforms, or large-scale data processing technologies.
• Knowledge of enterprise compliance, governance, and security review processes.
• Exposure to reliability engineering practices such as resilience testing or disaster recovery exercises.

Key Responsibilities

Product Design & Development

• Lead the mechanical design and development of new products and product enhancements.
• Create innovative concepts and translate them into detailed mechanical designs.
• Develop modular hardware architectures and reusable design solutions.
• Design complex mechanical systems, assemblies, and mechanisms while balancing performance, cost, manufacturability, and reliability.
• Convert product and customer requirements into practical engineering solutions.

Engineering Analysis & Validation

• Perform engineering calculations and technical analyses on components and assemblies.
• Identify technical risks early and develop effective mitigation plans.
• Develop and execute testing strategies, validation plans, and prototype evaluations to verify design performance.
• Ensure quality and reliability considerations are incorporated throughout the design process.

Project Execution

• Manage mechanical development schedules and deliverables for assigned projects.
• Support project planning activities and ensure designs are delivered on time and within budget.
• Collaborate with stakeholders to define product specifications and technical requirements.
• Drive continuous improvement initiatives and contribute to value engineering efforts.

Manufacturing & Production Support

• Work closely with manufacturing teams to support product industrialization and production readiness.
• Provide expertise in manufacturing processes including injection molding, machining, sheet metal fabrication, assembly, and related production methods.
• Troubleshoot manufacturing and product performance issues and implement design improvements when required.

Cross-Functional Collaboration

• Partner with Electrical, Firmware, Software, Manufacturing, Quality, and Product teams throughout the product development cycle.
• Participate in design reviews and contribute to multidisciplinary problem-solving efforts.
• Mentor and provide technical guidance to junior engineers where appropriate.

Requirements

Education & Experience

• Bachelor's degree in Mechanical Engineering or a related discipline.
• 8+ years of experience in mechanical product design and development.
• Proven experience taking products from concept and prototype stages through to mass production.

Technical Expertise

• Strong understanding of mechanical engineering principles and product development methodologies.
• Experience designing complex mechanisms such as:Gear trainsClutchesCamsLinkagesMotion-control systems
• Knowledge of electro-mechanical systems, including:MotorsSensorsPower transmission components
• Hands-on experience designing:Plastic componentsSheet metal partsDie-cast componentsRubber componentsMechanical assembliesElectro-mechanical assemblies
• Proficiency with SolidWorks and/or other 3D CAD tools.
• Familiarity with simulation and analysis tools (FEA preferred).
• Strong understanding of GD&T (Geometric Dimensioning & Tolerancing).

Preferred Qualifications

• Knowledge of Design of Experiments (DOE) and Six Sigma methodologies.
• Experience with:DFMEA (Design Failure Mode & Effects Analysis)Design for Manufacturing (DFM)Design for Assembly (DFA)Structured product evaluation and decision-making methodologies