Total 2 qa engineer job vacancies in Maintenance / Repair category in edb sg singapore

We seek individuals with highly developed conceptual, strategic, and analytical skills, capable of striking a balance between visionary thinking and practical solutions. The ability to comprehend, inspire, and mobilize others is crucial. A business-oriented mindset coupled with effective storytelling will drive your success. We are looking for self-starters ready to take on responsibilities with enthusiasm.

As an ML Engineer, your pivotal role involves operationalizing ML Models developed by Bank data scientists. You will serve as the focal point for ML model refactoring, optimization, containerization, deployment, and quality monitoring. Your main responsibilities will include:
Conduct reviews for compliance of the ML models in accordance with overall platform governance principles such as versioning, data / model lineage, code best practices and provide feedback to data scientists for potential improvements

Develop pipelines for continuous operation, feedback and monitoring of ML models leveraging best practices from the CI/CD vertical within the MLOps domain. This can include monitoring for data drift, triggering model retraining and setting up rollbacks.

Optimize AI development environments (development, testing, production) for usability, reliability and performance.

Have a strong relationship with the infrastructure and application development team in order to understand the best method of integrating the ML model into enterprise applications (e.g., transforming resulting models into APIs).

Work with data engineers to ensure data storage (data warehouses or data lakes) and data pipelines feeding these repositories and the ML feature or data stores are working as intended.

Evaluate open-source and AI/ML platforms and tools for feasibility of usage and integration from an infrastructure perspective. This also involves staying updated about the newest developments, patches and upgrades to the ML platforms in use by the data science teams.

• Proficiency in Python used both for ML and automation tasks
• Good knowledge of Bash and Unix/Linux command-line toolkit is a must-have.
• Hands on experience building CI/CD pipelines orchestration by Jenkins, GitLab CI, GitHub Actions or similar tools is a must-have.
• Knowledge of OpenShift / Kubernetes is a must-have.
• Good understanding of ML libraries such as Panda, NumPy, H2O, or TensorFlow.
• Knowledge in the operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g., Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, Dataiku, H2O, or DKube).
• Knowledge of Distributed Data Processing framework, such as Spark, or Dask.
• Knowledge of Workflow Orchestrator, such as Airflow or Ctrl-M.
• Knowledge of Logging and Monitoring tools, such as Splunk and Geneos.
• Experience in defining the processes, standards, frameworks, prototypes and toolsets in support of AI and ML development, monitoring, testing and operationalization.
• Experience in ML operationalization and orchestration (MLOps) tools, techniques and platforms. This includes scaling delivery of models, managing and governing ML Models, and managing and scaling AI platforms.

Role based in Sydney, Australia - Relocation Support Provided

We are Rokt, a hyper-growth ecommerce leader. We enable companies to unlock value by making each transaction relevant at the moment that matters most, when customers are buying. Together, Rokt's AI-based relevance Platform and scaled ecommerce Network powers billions of transactions. In December 2022, Rokt’s valuation increased to $2.4 billion USD, allowing us to expand rapidly across 15 countries. 

The Rokt engineering team builds best-in-class ecommerce technology that provides personalized and relevant experiences for customers globally and empowers marketers with sophisticated, AI-driven tooling to better understand consumers. Our bespoke platform handles millions of transactions per day and considers billions of data points which give engineers the opportunity to build technology at scale, collaborate across teams and gain exposure to a wide range of technology.

At Rokt, we practice transparency in career paths and compensation.

At Rokt, we believe in transparency, which is why we have a well-defined career ladder with transparent compensation and clear career paths based on competency and ability. Rokt’stars constantly strive to raise the bar, pushing the envelope of what is possible.

We are looking for a Senior Machine Learning Engineer

Compensation: $190,000-$235,000 AUD including superannuation, plus employee equity plan grant & world class benefits.

As a Senior Machine Learning Engineer, you are someone who has significant expertise in both machine learning and software engineering. You will be working with our engineering and product teams to design, build and productionise proprietary machine learning models to solve different business challenges including smart bidding, lookalike modelling, forecasting, etc.

About the Role:

• Collaborate closely with product managers and other engineers to understand business priorities, frame machine learning problems, and architect machine learning solutions.
• Build and productionise machine learning models including data preparation/processing pipelines, machine learning orchestrations, improvements of services performance and reliability and etc.
• Contribute and maintain the high quality of the code base with tests that provide a high level of functional coverage as well as non-functional aspects with load testing, unit testing, integration testing, etc.
• Keep track of emerging tech and trends, research the state-of-art deep learning models, prototype new modelling ideas, and conduct offline and online experiments.
• Share your knowledge by giving brown bags, tech talks, and evangelising appropriate tech and engineering best practices.

About You:

• PhD in Machine Learning [Nice to have]
• Extensive knowledge in and experience with some of the following areas - Bayesian methods, Recommender systems, multi-task modelling, meta-learning, click through rate modelling or conversion rate modelling.
• 3+ years of industry experience in building production-grade machine learning systems with all aspects of model training, tuning, deploying, serving and monitoring.
• Experience with Kubeflow (or similar), Tensorflow and Feature Store in a production environment is a massive plus.
• Bonus points if you are familiar with any of the following architectures or have experience with the models mentioned in this benchmark: DCNV2, MMOE, Deep & Wide, ESMM, xDeepFM, and GDCN.

This role is based in Sydney, Australia. Rokt will provide relocation and visa support to qualified candidates.

About Rokt’stars:

As a mission-driven, hyper-growth community of curious explorers, our ambition is to unlock the full potential in ecommerce and beyond. Our bias for action means we are not afraid to quickly venture into uncharted territories, take risks or challenge the status quo; in doing so we either win or learn. We work together as one aligned team never letting egos get in the way of brilliant ideas. We value diversity, transparency and smart humble people who enjoy building a disruptive business together. We pride ourselves on being a force for good as we make the world better. 

About The Benefits:

We leverage best-in-class technology and market-leading innovation in AI and ML, with all of that being underlined by building and maintaining a fantastic and inclusive culture where people can be their authentic selves, and offering a great list of perks and benefits to go with it:

• Accelerate your career. We offer roadmaps to leadership and an annual $5000 training allowance
• Become a shareholder. Every Rokt’star gets equity in the company
• Enjoy catered lunch every day and healthy snacks in the office. Plus join the gym on us! 
• Extra leave (bonus annual leave, sabbatical leave etc.) 
• Work with the greatest talent in town
• See the world! We have offices in New York, Seattle, Sydney, Tokyo and London

We believe we’re better together. We love spending time together and are in the office most days (teams are in the office 4 days per week). We also get that you need to balance your life and your commitments so you have the flexibility to manage your own hours and can spend up to a week of every quarter working from anywhere.

If this sounds like a role you’d enjoy, apply here and you’ll hear from our recruiting team.