Vacancies

Location: Singapore Employment Type: Full-time   About the Role We are seeking a highly experienced Senior Machine Learning Engineer with 8–15 years of expertise in designing, building, and scaling machine learning solutions. Based in Singapore, you will play a key role in leading the architecture, development, and deployment of AI/ML systems that drive innovation and deliver measurable business outcomes. You will mentor junior engineers, collaborate closely with data scientists, and partner with business stakeholders to ensure ML solutions are production-ready, secure, and scalable.   Key Responsibilities

• Lead the design and deployment of end-to-end machine learning solutions, from data ingestion and feature engineering to production deployment and monitoring
• Architect scalable ML pipelines and implement MLOps best practices (automation, CI/CD for ML, model monitoring, retraining strategies)
• Collaborate with cross-functional teams (data scientists, data engineers, product managers, business stakeholders) to translate business challenges into technical ML solutions
• Optimize ML models for performance, interpretability, and cost efficiency
• Drive adoption of best practices in model governance, security, and ethical AI
• Stay ahead of industry trends in AI, deep learning, NLP, computer vision, and large-scale ML systems
• Mentor and guide junior and mid-level engineers, fostering technical excellence across the team
• Provide technical leadership in evaluating tools, frameworks, and platforms for enterprise ML use cases

  Requirements

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field (PhD is a plus)
• 8–15 years of professional experience in machine learning engineering, data science, or AI-driven software development
• Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, Scikit-learn
• Deep expertise in building production-grade ML pipelines using cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML) and containerization (Docker, Kubernetes)
• Proven experience implementing MLOps (MLflow, Kubeflow, or similar)
• Solid understanding of big data platforms (Spark, Hadoop, Kafka) and real-time data processing
• Experience leading large-scale AI/ML projects, including model deployment in enterprise environments
• Excellent problem-solving skills and ability to balance innovation with practical business needs
• Strong communication skills in English, with the ability to engage technical and non-technical stakeholders

  Nice-to-Have

• Hands-on experience in NLP, computer vision, recommendation systems, or generative AI (LLMs, transformers)
• Exposure to financial services, healthcare, or other regulated industries with strict compliance requirements
• Experience building and leading ML/AI teams
• Familiarity with data privacy, responsible AI frameworks, and explainable AI techniques

  What We Offer

• Attractive compensation and benefits tailored for senior professionals
• Opportunity to lead mission-critical AI/ML projects with regional and global impact
• Professional growth towards ML Architect or AI Leader roles
• Sponsorship for continuous learning, certifications, and industry events
• A collaborative and innovative environment that values thought leadership and mentorship

Location: Doha, Qatar Employment Type: Full-time   About the Role We are seeking a highly experienced Trading Business Analyst to join our team in Doha, Qatar. The ideal candidate will have strong hands-on experience with Endur, programming knowledge, and deep expertise in the energy trading domain. This role will act as a bridge between trading business users and technology teams, ensuring that system enhancements and solutions align with business requirements, regulatory standards, and industry best practices.   Key Responsibilities

• Collaborate with trading, risk, operations, and IT teams to gather, document, and translate business requirements into functional and technical solutions
• Provide subject matter expertise in Endur, including configuration, workflows, and extensions
• Develop and customize Endur solutions using AVS and JVS programming
• Support the full trade life cycle, including trade capture, validation, risk management, confirmations, settlements, and reporting
• Contribute to projects related to derivatives trading, ensuring compliance with business, risk, and regulatory requirements
• Work with stakeholders to design process improvements, automation opportunities, and system enhancements
• Create functional specifications, manage UAT, and support deployment of new features and upgrades
• Troubleshoot and resolve Endur-related issues, providing root cause analysis and guidance to developers

  Requirements

• Bachelor’s or Master’s degree in Finance, Business, Computer Science, or related discipline
• Proven experience with Endur (configuration, extension, and implementation)
• Hands-on programming experience with AVS/JVS within Endur
• Strong knowledge of the energy trading domain, ideally including LNG, oil, gas, or power
• Solid understanding of derivatives trading and risk management concepts
• Strong knowledge of trade life cycle management, from deal capture through to settlement and reporting
• Excellent analytical, problem-solving, and communication skills
• Ability to work effectively in a fast-paced trading environment with multinational teams

  Nice-to-Have

• Exposure to regulatory reporting requirements (EMIR, Dodd-Frank, REMIT, etc.)
• Experience integrating Endur with third-party systems (risk, settlement, or accounting platforms)
• Familiarity with SQL, Python, or other scripting languages for data analysis and reporting
• Experience working in Agile/Scrum delivery models

  What We Offer

• Competitive tax-free salary and comprehensive benefits package
• Opportunity to work on front-to-back trading projects in a leading energy hub
• Career development and training opportunities in trading systems and business analysis
• Exposure to global energy trading practices and markets
• A dynamic, multicultural work environment in Doha, Qatar