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Senior Machine Learning Infrastructure Engineer | Fintech

OptasiaAthens, Attica, Greece
On-site Full-time

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Experience Level

Senior

Qualifications

Qualifications:Proven experience in ML infrastructure and engineering. Strong knowledge of machine learning algorithms and statistical methods. Experience with big data technologies (Spark, Hadoop). Proficiency in programming languages such as Python, Scala, or Java. Experience with CI/CD tools like Jenkins. Familiarity with container orchestration tools (Docker, Kubernetes) is a plus. Excellent problem-solving skills and ability to work collaboratively in a team environment. Strong communication skills to convey complex technical concepts. Passion for continuous learning and staying updated with industry trends.

About the job

Optasia is an innovative B2B2X financial technology platform dedicated to enhancing scoring, financial decision-making, disbursement, and collection processes. Our mission is to foster financial inclusion for everyone. Join us in transforming the financial landscape!

We are on the lookout for passionate and driven professionals who thrive in a collaborative environment. As a member of our dynamic team, you will contribute to delivering innovative solutions that make a difference.

Data plays a pivotal role in Optasia's growth strategy, with our ML Engineering team being a key contributor. We harness data from various sources into our extensive big data clusters and develop and manage multiple analytical pipelines using state-of-the-art big data technologies.

As a Senior ML Infrastructure Engineer, you will play a crucial role in enhancing Optasia's data-driven decision-making and credit risk management by developing and optimizing scalable, end-to-end ML pipelines. Your key responsibilities will include: (i) building robust ML pipelines, (ii) designing statistical and machine learning algorithms, and (iii) operationalizing these solutions to bolster credit risk management, directly impacting Optasia's success.

Your Responsibilities:

  • Provide technical guidance in ML engineering to ensure the adoption of optimal tools and methodologies, staying ahead of emerging trends and delivering industry-leading solutions.
  • Enhance the scalability, stability, accuracy, speed, and efficiency of ML workflows while maintaining stringent testing and code quality standards.
  • Contribute to the design and development of microservices and tools that facilitate the Machine Learning lifecycle at Optasia.
  • Collaborate on the design and implementation of scalable, real-time microservices utilized globally.
  • Foster continuous improvements in the development lifecycle with the team.
  • Design, develop, and maintain large-scale Spark jobs using PySpark and Scala.
  • Build and manage CI/CD pipelines with Jenkins.
  • Create automation scripts using Python or Bash.
  • Develop and deploy scalable Airflow pipelines to support the Machine Learning lifecycle.
  • Conduct data exploration and analysis to scope, build, and refine Machine Learning proof-of-concepts (PoCs).
  • Partner with Engineers and the Credit Risk team to design and implement solutions that deliver business value at Optasia.
  • Optimize the codebase through Spark job tuning and refactoring.
  • Drive enhancements to our feature engineering engine for improved efficiency.

About Optasia

Optasia is at the forefront of the fintech revolution, providing solutions that empower individuals and organizations through advanced financial tools. Our commitment to innovation and excellence drives us to create a more inclusive financial ecosystem for all.

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