Staff Advanced Quality Engineer (Software)

Senior Machine Learning Engineer (Production & MLOps Focus)

Testing

Responsibilities: QMS Ownership for Deliverable Software <ul><li>Translate AS9115 Rev A and AS9100:2016 requirements into practical procedures, work instructions, and templates.</li><li>Establish processes covering software planning, development, integration, verification/validation, release, delivery, and post-delivery support.</li><li>Ensure the QMS supports multiple development models (Agile, Waterfall, Incremental) while enforcing required quality controls including reviews, approvals, traceability, and documentation.</li></ul> Software Planning &amp; Requirements Quality <ul><li>Lead the creation and maintenance of Software Quality Plans.</li><li>Establish standards for requirements management ensuring requirements are:</li></ul> <ul><li>Clear</li><li>Unambiguous</li><li>Testable</li><li>Maintain bidirectional traceability from:</li><li>Requirements → Design → Code → Test → Release.</li></ul> Configuration Management &amp; Change Control Define standards for Software Configuration Management (CM) including: <ul><li>Baselines</li><li>Configuration item identification</li><li>Change evaluation and approval</li><li>Configuration status accounting</li><li>Integrate software configuration management with product and system configuration processes.</li><li>Ensure CM covers software, documentation, tools, environments, and build/release artifacts.</li></ul> Supplier &amp; COTS/NDS Management <ul><li>Establish standards for evaluation and acceptance of Commercial Off-The-Shelf (COTS) and Non-Developmental Software (NDS) used in deliverable products.</li><li>Define AS9115 control applicability with both customers and suppliers.</li><li>Support supplier qualification, audits, and incoming verification for software deliverables and services.</li></ul> Verification, Validation &amp; Test Assurance <ul><li>Define verification standards within the QMS including:</li><li>Static analysis</li><li>Peer reviews</li><li>Unit testing</li><li>Integration testing</li><li>System testing</li><li>Regression testing</li><li>Security testing</li><li>Ensure independence of verification activities where required.</li><li>Maintain controlled test environments, data integrity, and objective evidence for compliance audits.</li></ul> Release, Delivery &amp; Post-Delivery Support Develop procedures for: <ul><li>Software release criteria</li><li>Delivery records</li><li>Installation documentation</li><li>Post-delivery issue management</li><li>Patching and configuration updates</li><li>Ensure all processes align with AS9115 standards.</li></ul> Audits, Metrics &amp; Continuous Improvement Lead internal and customer audits related to AS9115/AS9100 compliance. <ul><li>Manage Corrective and Preventive Actions (CAPA).</li><li>Support external and second-party audits with aerospace OEMs.</li><li>Define and track key quality KPIs, including:</li><li>Requirements volatility</li><li>Defect density</li><li>Defect escape rate</li><li>Verification coverage</li><li>Audit findings aging</li><li>Build reproducibility</li><li>Change lead time</li></ul> Requirements: Bachelor’s or Master’s degree in: <ul><li>Software Engineering</li><li>Computer Science</li><li>Systems Engineering or a related discipline.</li><li>Minimum 5 years of experience in software quality or software engineering within aerospace, defense, or other regulated industries.</li><li>Hands-on experience implementing AS9100 quality processes with working knowledge of AS9115 software lifecycle controls.</li></ul> Strong experience in: <ul><li>Requirements management</li><li>Configuration management</li><li>Verification and validation</li><li>Software release governance</li><li>Experience managing COTS/NDS software integration and supplier quality.</li><li>Proven ability to lead audit activities and corrective actions using structured problem-solving tools such as:</li><li>5 Why</li><li>Ishikawa</li><li>8D</li></ul> Preferred Qualifications <ul><li>Experience supporting AS9115 second-party audits with aerospace OEMs.</li><li>Familiarity with DO-178C concepts and coordination with DO-254/ED-80 hardware processes.</li><li>Experience with ALM/PLM and configuration management tools, such as:</li><li>Polarion</li><li>IBM DOORS</li><li>CodeBeamer</li><li>Git / GitLab</li><li>Bitbucket</li><li>Azure DevOps</li><li>Knowledge of CI/CD pipelines, static analysis tools, and unit testing frameworks.</li><li>Exposure to CMMI-DEV processes and experience aligning them with AS9115 quality objectives.</li></ul>

Responsibilities: <ul><li>Design, deploy, and maintain production-ready ML models and pipelines for real-world applications.&nbsp;</li><li>Build and scale ML pipelines using Vertex AI Pipelines, Kubeflow, Airflow, and manage infra-as-code with Terraform/Helm.&nbsp;</li><li>Implement automated retraining, drift detection, and re-deployment of ML models.&nbsp;</li><li>Develop CI/CD workflows (GitHub Actions, GitLab CI, Jenkins) tailored for ML.&nbsp;</li><li>Implement model monitoring, observability, and alerting across accuracy, latency, and cost.&nbsp;</li><li>Integrate and manage feature stores, knowledge graphs, and vector databases for advanced ML/RAG use cases.&nbsp;</li><li>Ensure pipelines are secure, compliant, and cost-optimized.&nbsp;&nbsp;</li><li>Drive adoption of MLOps best practices: develop and maintain workflows to ensure reproducibility, versioning, lineage tracking, governance .&nbsp;</li><li>Mentor junior engineers and contribute to long-term ML platform architecture design and technical roadmap.&nbsp;</li><li>Stay current with the latest ML research and apply new tools pragmatically to production systems.&nbsp;</li><li>Collaborate with product managers, DS, and engineers to translate business problems into reliable ML systems.&nbsp;</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field (PhD is a plus).&nbsp;</li><li>5+ years of experience in machine learning engineering, MLOps, or large-scale AI/DS systems.&nbsp;</li><li>Strong foundations in data structures, algorithms, and distributed systems.&nbsp;</li><li>Proficient in Python (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.) and SQL.&nbsp;</li><li>Hands-on experience building and deploying ML models at scale in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML).&nbsp;</li><li>Experience with containerization (Docker, Kubernetes) and orchestration (Airflow, TFX, Kubeflow).&nbsp;</li><li>Familiarity with CI/CD pipelines, infrastructure-as-code (Terraform/Helm), and configuration management.&nbsp;</li><li>Experience with big data and streaming technologies (Spark, Flink, Kafka, Hive, Hadoop).&nbsp;</li><li>Practical exposure to model observability tools (Prometheus, Grafana, EvidentlyAI) and governance (WatsonX)&nbsp;</li><li>Strong understanding of statistical methods, ML algorithms, and deep learning architectures.&nbsp;</li></ul>

<h2>About the job</h2> About Tabsquare TabSquare provides AI-powered technology solutions for the F&amp;B industry. Through TabSquares solutions, restaurants can efficiently manage orders, process payments, and effectively engage with their customers. TabSquare assists partner restaurants in driving higher sales, streamlining operations, and delivering an enhanced customer experience. TabSquare is a market leader with operations in Singapore, Malaysia, Indonesia, Australia, the Philippines, Taiwan, Thailand, Hong Kong, Sweden, and the UAE. Trusted by thousands of restaurants, TabSquares clients include well-known F&amp;B brands such as Pizza Hut, KFC, Minor Food Group, Sushi Tei, Paradise Food Group, Japan Foods Holding, Zingrill Holdings, The Coffee Club, Old Town White Coffee, Secret Recipe, and many more. TabSquare is a wholly owned subsidiary of Delivery Hero, a global leader in the food delivery industry. For more information, visit <a href="http://www.tabsquare.ai/" rel="noopener noreferrer" target="_blank" style="color: var(--color-text);">http://www.tabsquare.ai</a> Responsibilities: <ul><li>Estimate, plan, prioritize and coordinate testing activities for the cross functional QA team.</li><li>Review requirements, specifications or design documents to provide timely and meaningful feedback</li><li>Create detailed, comprehensive, and well-structured documentations, test plans and test cases.</li><li>To perform system testing and end-user testing on our suite of solutions (end to end); comprising web-based applications, mobile apps on both Android and iOS platforms.</li><li>Track QA metrics, like defect densities and open defect counts and do updates on daily, weekly and monthly basis. </li><li>Design, develop and execute Automation Scripts using Katalon Studio / Selenium or similar tools.</li><li>Support and manage UAT, Sanity, Regression activities in multiple environments.</li><li>Monitor, debug and compare the system logs, error using Datadog in multiple environments.</li><li>Work closely with the stakeholders, engineering team and also the product team, to ensure the quality/stability of the software releases.</li><li>Research on new technologies or market trends, to be able to propose new solutions/features, recommendations or ideas to improve the software solution.</li><li>Adopts and improves all required QA Processes, SOP and Ground Rules as needed.</li><li>Perform other relevant duties as assigned by Head/Managers.</li></ul> The Employee, as per business needs, may be required to undertake any other such duties as may be assigned in line with the employee’s position, skills, and capabilities. Requirements: <ul><li>Bachelors degree in Computer Science / Application or related major.</li><li>Minimum 4-6 years of hands-on experience in Manual &amp; Automation Testing.</li><li>Excellent communication skills and a good command of English.</li><li>Self-motivated, detail-oriented, with strong analytical and problem solving skills. Able to work independently with minimum supervision.</li><li>Good understanding of the software development, testing &amp; bug life cycle process.</li><li>Strong technical experience and ability to automate tests using Java, JS or Python.</li><li>Technical experience with API’s, JSON, SQL, HTML and tools like Postman to check &amp; validate test results.</li><li>Technical experience with CI/CD tools like Jenkins, Gitlab and Load Test tools like Locust, JMeter.</li></ul> Tools / Technology: Selenium, Cucumber, Java, Rest Assured, Katalon, Appium, JMeter, Locust, TestRail, Datadog, PostMan, Sequel Pro, Slack, Atlassian.

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Staff Advanced Quality Engineer (Software)

Senior Machine Learning Engineer (Production & MLOps Focus)

Testing

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Staff Advanced Quality Engineer (Software)

Senior Machine Learning Engineer (Production & MLOps Focus)

Testing

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