Position Summary: We are looking for a Senior Database Developer with strong experience in migrating IBM DB2 databases to AWS RDS Aurora PostgreSQL . If you're passionate about cloud modernization and database engineering, and you're ready to lead high-impact migration projects, we want to hear from you! Key Responsibilities: Lead end-to-end migration of on-premise DB2 databases to AWS RDS Aurora PostgreSQL Design, implement, and optimize migration strategies and database schemas Collaborate with cross-functional teams (Cloud Architects, Developers, DevOps) Build and manage automation scripts/tools for data transformation and validation Assess current database structures and align them with AWS & PostgreSQL best practices Monitor and optimize post-migration performance Troubleshoot migration issues and ensure data integrity Maintain security, compliance, and governance throughout the project lifecycle Produce comprehensive documentation (migration plans, data maps, rollback strategies) Mentor junior database engineers Required Qualifications: Bachelor’s or Master’s degree in Computer Science or related field 7+ years of experience in database development/administration Deep knowledge of IBM DB2 and its architecture Proven hands-on experience migrating DB2 to AWS RDS Aurora PostgreSQL Strong PostgreSQL skills: stored procedures, indexing, performance tuning Proficiency in ETL tools , scripting (Python, Shell), and automation Hands-on with AWS DMS , Schema Conversion Tool , RDS , Aurora Strong understanding of data modeling and optimization techniques Excellent analytical and communication skills Preferred Qualifications: AWS Certification (e.g., AWS Certified Database – Specialty or Solutions Architect) Experience with CI/CD , Infrastructure-as-Code (Terraform, CloudFormation) Familiarity with DevOps tools (Git, Jenkins, Ansible) Why Join Us? Work with a global leader in cloud and software solutions Be part of cutting-edge migration projects across industries Join a culture that celebrates collaboration, innovation, and growth Competitive compensation and career development opportunities Open to candidates who are willing to relocate to Malaysia.
Overview We are seeking an experienced AI Lead to drive the design, development, and deployment of advanced machine learning solutions with a focus on model fine-tuning, personalization at scale, and federated learning frameworks. This role requires a deep understanding of distributed ML systems, privacy-preserving training, and scalable deployment strategies. The AI Lead will collaborate with data engineering and product teams to build enterprise-grade AI systems that balance accuracy, efficiency, and compliance. Key Responsibilities Lead end-to-end model fine-tuning initiatives, adapting foundation models (LLMs, vision models, multimodal models) to domain-specific datasets. Architect and implement federated learning pipelines to enable on-device and cross-organization collaboration while maintaining strict data privacy standards. Research and apply parameter-efficient fine-tuning techniques (LoRA, adapters, prompt-tuning, quantization) for cost-effective customization. Collaborate with data engineering teams to streamline model training across distributed and heterogeneous data sources. Drive MLOps practices for monitoring, updating, and retraining fine-tuned models in production environments. Evaluate trade-offs between centralized training, decentralized (federated) learning, and hybrid approaches to optimize both performance and compliance. Stay updated with advancements in federated optimization algorithms, privacy-preserving techniques (differential privacy, secure aggregation), and model governance frameworks. Mentor junior engineers and act as the technical authority for applied AI and federated learning strategies within the organization. Required Qualifications Master’s or PhD in Computer Science, Machine Learning, Artificial Intelligence, or related fields. 6+ years of professional experience in machine learning/AI, with at least 2 years leading teams or solutions. Strong expertise in model fine-tuning (transformers, diffusion models, or large multimodal models). Hands-on experience with federated learning frameworks (TensorFlow, Federated, PySyft, Flower, FedML). Deep knowledge of privacy-preserving ML methods: differential privacy, homomorphic encryption, secure MPC. Proficiency in PyTorch/TensorFlow, distributed training (Horovod, DeepSpeed), and orchestration tools (Kubernetes, Ray). Familiarity with MLOps stack: MLflow, Kubeflow, SageMaker, or Databricks. Strong publications, patents, or conference exposure in ML systems or federated learning is a plus. Preferred Skills Experience deploying federated learning at scale in mobile, enterprise, or IoT environments. Knowledge of regulatory compliance frameworks for AI (GDPR, HIPAA, data localization laws). Strong understanding of edge computing and on-device model optimization (quantization, pruning, distillation). Leadership capability to translate research concepts into production-ready enterprise AI products. Role Impact The AI Lead will play a pivotal role in bridging cutting-edge research with enterprise adoption, enabling organizations to leverage foundation models without compromising data privacy. This role will accelerate the adoption of federated learning-driven AI systems that scale across industries such as healthcare, finance, and retail.
Job Title: Data Scientist Experience Level: (3-5 years) Position Summary: We are looking for an experienced Data Scientist with 3-5 years of experience to join our team. You will be responsible for applying statistical methods and machine learning to solve key business challenges. Your work will involve analyzing complex datasets, building predictive models, and communicating your findings to stakeholders. Key Responsibilities: ● Collaborate with business teams to identify and frame data science problems. ● Develop, validate, and deploy machine learning models and predictive algorithms. ● Perform deep exploratory data analysis (EDA) to generate insights. ● Present findings and recommendations to both technical and non-technical audiences. ● Contribute to the entire machine learning lifecycle, from ideation to production deployment. Required Qualifications: ● Education: Bachelor's or Master's degree in a quantitative field. ● Experience: 3-5 years as a Data Scientist or in a similar role. Technical Skills: ● Strong proficiency in Python and its data science libraries (e.g., pandas, scikit-learn). ● Solid understanding of machine learning algorithms and statistical concepts. ● Expertise in SQL for data manipulation and querying. ● Experience with data visualization tools (e.g., Tableau, Power BI). Soft Skills: ● Excellent problem-solving and communication skills. ● Ability to work effectively both independently and in a team. Preferred Qualifications: ● Experience with cloud platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g., Spark). ● Knowledge of MLOps principles and tools.
Job Summary: We are seeking an experienced Senior Database Developer with deep expertise in DB2 databases and proven experience in migrating on-premises databases to AWS RDS Aurora PostgreSQL. The ideal candidate will play a key role in modernizing our database infrastructure, leading large-scale migrations, and ensuring data integrity, performance, and scalability throughout the process. Key Responsibilities: Lead the end-to-end migration of IBM DB2 databases from on-premises environments to AWS RDS Aurora PostgreSQL. Design, implement, and optimize database schemas and migration strategies for performance and reliability. Work closely with cloud architects, application developers, and DevOps teams to ensure smooth data transitions. Develop scripts and tools to automate data conversion, transformation, and validation processes. Assess existing database structures and suggest improvements to align with AWS best practices and PostgreSQL standards. Monitor and tune database performance post-migration. Troubleshoot complex migration issues and data anomalies. Ensure security, compliance, and data governance standards are met throughout the migration lifecycle. Create detailed documentation including migration plans, data mappings, and rollback strategies. Provide guidance and mentorship to junior database engineers as needed. Required Qualifications: Bachelor’s or master’s degree in computer science, Information Systems, or related field. 7+ years of experience in database development and management. Strong hands-on experience with IBM DB2 database architecture and administration. Proven experience in migrating DB2 databases to AWS RDS Aurora PostgreSQL. Expertise in PostgreSQL development, including stored procedures, functions, indexing, and performance tuning. Proficient in ETL tools, data transformation, and scripting languages (Python, Shell, or equivalent). Familiarity with AWS services such as DMS (Database Migration Service), Schema Conversion Tool, RDS, and Aurora. Strong understanding of data modelling, normalization, and database optimization techniques. Excellent problem-solving skills and attention to detail. Strong verbal and written communication skills. Preferred Qualifications: AWS Certification (e.g., AWS Certified Database – Specialty, AWS Certified Solutions Architect). Experience with CI/CD practices and infrastructure as code (Terraform, CloudFormation). Familiarity with DevOps tools and concepts (e.g., Git, Jenkins, Ansible). Candidates are willing to relocate to Malaysia are encouraged to apply
Presales Data & AI Solution Architect (Microsoft Solutions) – 5 Years’ Experience Role Summary The Presales Data & AI Solution Architect partners with customers and internal sales teams to design, present, and enable advanced Data & AI solutions leveraging the Microsoft ecosystem (Azure, Fabric, and related technologies). This role bridges business needs with technical possibilities, supporting the end-to-end solution sales cycle with architectural vision, technical depth, and a focus on value realization. Key Responsibilities Engage with clients to understand business objectives, data landscape, and technical requirements. Lead architecture design sessions, create solution blueprints, and guide Data & AI roadmaps (including cloud migration, data modernization, governance, and AI adoption). Design and prototype secure, scalable solutions using Microsoft technologies: Azure Data Services, Azure AI, Microsoft Fabric, Synapse, Databricks, and relevant database systems. Deliver technical presentations, demos, and proof-of-concept engagements for customers; address customer challenges and blockers. Collaborate with sales teams to define technical win strategies, proposal offerings, and competitive differentiators. Support production readiness, health, and optimization of data and AI workloads – including AI agent and ML model integration as appropriate. Act as technical advisor—mentoring clients and internal teams, documenting architectures and presenting to technical/non-technical audiences. Required Qualifications Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent experience). 5 years’ experience in data, analytics, or AI solution architecture, with proven exposure to Microsoft Azure and Data/AI workloads. Track record designing, implementing, or supporting solutions on Azure (Databases, Analytics, AI/ML, Data Lakes, Fabric, Synapse, etc.). Pre-sales experience: technical sales engagements, RFP/RFI responses, building prototypes and customer demos. Strong customer-facing presentation/consultation skills and the ability to build technical trust. Proficient with solution design patterns for cloud data platforms, data integration, governance, analytics, and security. Experience with enterprise data modeling, SQL, Python/Scala, and AI/ML frameworks is a plus. Preferred/Bonus Skills Microsoft certifications in Data & AI/Cloud Solution Architecture. Experience with agentic-AI, Copilot integrations, or large language model solutions. Familiarity with Power BI, Fabric, and ecosystem tools. Prior consulting, technical workshops, or enablement delivery background. Work Style Comfort working in both client-facing and internal leadership settings. Ability to manage multiple presales engagements concurrently. Passion for continuous learning and staying current with Microsoft Data & AI innovations.
Presales Data & AI Solution Architect (Microsoft Solutions) 5 Years Experience Role Summary The Presales Data & AI Solution Architect partners with customers and internal sales teams to design, present, and enable advanced Data & AI solutions leveraging the Microsoft ecosystem (Azure, Fabric, and related technologies). This role bridges business needs with technical possibilities, supporting the end-to-end solution sales cycle with architectural vision, technical depth, and a focus on value realization. Key Responsibilities Engage with clients to understand business objectives, data landscape, and technical requirements. Lead architecture design sessions, create solution blueprints, and guide Data & AI roadmaps (including cloud migration, data modernization, governance, and AI adoption). Design and prototype secure, scalable solutions using Microsoft technologies: Azure Data Services, Azure AI, Microsoft Fabric, Synapse, Databricks, and relevant database systems. Deliver technical presentations, demos, and proof-of-concept engagements for customers; address customer challenges and blockers. Collaborate with sales teams to define technical win strategies, proposal offerings, and competitive differentiators. Support production readiness, health, and optimization of data and AI workloads including AI agent and ML model integration as appropriate. Act as technical advisormentoring clients and internal teams, documenting architectures and presenting to technical/non-technical audiences. Required Qualifications Bachelor's degree in Computer Science, Engineering, Data Science, or a related field (or equivalent experience). 5 years experience in data, analytics, or AI solution architecture, with proven exposure to Microsoft Azure and Data/AI workloads. Track record designing, implementing, or supporting solutions on Azure (Databases, Analytics, AI/ML, Data Lakes, Fabric, Synapse, etc.). Pre-sales experience: technical sales engagements, RFP/RFI responses, building prototypes and customer demos. Strong customer-facing presentation/consultation skills and the ability to build technical trust. Proficient with solution design patterns for cloud data platforms, data integration, governance, analytics, and security. Experience with enterprise data modeling, SQL, Python/Scala, and AI/ML frameworks is a plus. Preferred/Bonus Skills Microsoft certifications in Data & AI/Cloud Solution Architecture. Experience with agentic-AI, Copilot integrations, or large language model solutions. Familiarity with Power BI, Fabric, and ecosystem tools. Prior consulting, technical workshops, or enablement delivery background. Work Style Comfort working in both client-facing and internal leadership settings. Ability to manage multiple presales engagements concurrently. Passion for continuous learning and staying current with Microsoft Data & AI innovations.