Senior Machine Learning Infrastructure Engineer, Fintech

Optasia is a fully enabled B2B2X financial technology platform covering scoring, financial decisioning, disbursement and collection. We are committed to enabling financial inclusion for all. We are changing the world our way.

We are seeking for enthusiastic professionals, with energy, who are results driven and have can-do attitude, who want to be part of a team of likeminded individuals who are delivering solutions in an innovative and exciting environment.

Data is at the core of Optasia growth plan and the ML Engineering team is a significant contributor to Optasia’s success and growth, achieved through data driven insights and decision making. We are currently leveraging and ingesting data from multiple sources into our large-scale big data clusters and develop and run multiple analytical pipelines, over a state-of-the art big data technology stack.

We are looking for a Senior ML Infrastructure Engineer to join our growing ML Engineering team. In this role, you will help advance Optasia’s data-driven decision-making and credit risk management by building and evolving scalable, end-to-end ML pipelines. The main responsibilities include (i) building robust ML pipelines , (ii) designing and developing statistical and machine learning algorithms, and (iii) operationalizing these solutions to strengthen in credit risk management - directly contributing to Optasia’s success.

What you will do

• Offer technical expertise in ML engineering, helping the team adopt the right tools and approaches, stay ahead of emerging trends, and deliver solutions that meet industry best practices.
• Provide expert guidance to improve the scalability, stability, accuracy, speed, and efficiency of ML workflows, while upholding the highest standards of testing and code quality.
• Contribute to the design and development of the microservices and tools that support Machine Learning lifecycle at Optasia.
• Contribute to the design and delivery of scalable, real-time microservices used globally.
• Drive continuous improvements in the development lifecycle in collaboration with the team.
• Design, develop and maintain large-scale Spark jobs using PySpark and Scala.
• Build and manage CI/CD pipelines with Jenkins.
• Develop automation scripts using Python or Bash.
• Develop and deploy scalable Airflow pipelines that support the Machine Learning lifecycle.
• Perform data exploration and analysis to scope, build, and iterate on Machine Learning proof-of-concepts (PoCs).
• Partner with Engineers and Credit Risk team to design and deliver solutions that drive business value at Optasia.
• Optimize the codebase through Spark job tuning and refactoring.
• Drive improvements to our feature engineering engine to support more efficient ML workflows.

What you will bring

• Bachelor's or Master's degree in Electrical Engineering, Computer Science or Informatics.
• 5+ years of industry experience with Machine Learning Engineering and MLOps background.
• Solid understanding of core Machine Learning concepts and MLOps.
• Proficiency in Python and PySpark (or Scala, Java).
• Strong knowledge of the Hadoop ecosystem.
• Proficiency in SQL.
• Proficiency in Linux.
• Strong knowledge of end-to-end API development and deployment.
• Proficiency in building and managing Dockerized applications.
• Experience with workflow orchestration tools such as Airflow (or similar).
• Familiarity with CI/CD best practices.
• Ability to meet tight deadlines, work under pressure, and maintain strict attention to detail.
• Awareness of emerging technologies, with the ability to quickly learn and adapt to new tools and frameworks

Why you should apply

What we offer:

Flexible remote working

Competitive remuneration package

Extra day off on your birthday

Performance-based bonus scheme

Comprehensive private healthcare insurance

All the tech gear you need to work smart

Optasia’s Perks:

Be a part of a multicultural working environment

Meet a very unique and promising business and industry

Gain insights for tomorrow market’s foreground

A solid career path within our working family is ready for you

Continuous training and access to online training platforms

CSR activities and festive events within any possible occasion

Enjoy comfortable open space restaurant with varied meal options every day

Wellbeing activities access such as free on-site yoga classes, plus available squash court on our premises

In accordance with applicable pay transparency requirements, the salary range for this position will be communicated to candidates before the first step of the selection process, enabling informed discussions regarding the role.