Senior Machine Learning Infrastructure Engineer, Fintech

Optasia Group

Kentucky

On-site

USD 100,000 - 140,000

Full time

14 days+

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Benefits offered by this job

Flexible remote working
Competitive remuneration package
Extra day off on your birthday
Performance-based bonus scheme
Comprehensive private healthcare insurance
All necessary tech gear for work

Job summary

A progressive financial technology firm is seeking a Senior ML Infrastructure Engineer in Kentucky. The role involves building scalable ML pipelines, operationalizing solutions for credit risk management, and working on large-scale data analytics. Ideal candidates have 5+ years in ML engineering, a solid grasp of Python and PySpark, and are familiar with CI/CD practices. Flexible remote work and a competitive salary are part of the offer.

Qualifications

  • 5+ years of industry experience with Machine Learning Engineering and MLOps background.
  • Solid understanding of core Machine Learning concepts and MLOps.
  • Ability to meet tight deadlines and work under pressure.

Responsibilities

  • Build robust ML pipelines and operationalize solutions for credit risk management.
  • Design and develop statistical and machine learning algorithms.
  • Maintain large-scale Spark jobs using PySpark and Scala.

Skills

Machine Learning Engineering
MLOps
Python
PySpark
Scala
SQL
Hadoop ecosystem
API development
Docker
Airflow

Education

Bachelor's or Master's degree in Electrical Engineering, Computer Science or Informatics

Tools

Linux
Jenkins

Job description

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

Optasia’s Values 🌟

#1 Drive to Thrive: Fully dedicated to evolving. We welcome all challenges and learning opportunities.
#2 Customer-First Mindset: We go above and beyond to meet our partners’ and clients’ expectations.
#3 Bridge the Gap: Knowledge is shared, information is exchanged and every opinion counts.
#4 Go-Getter Spirit: We are results oriented. We identify any shortcomings that hold us back and step up to do what’s needed.
#5 Together we will do it: We are committed to supporting one another and to understanding and respecting different perspectives, as we aim to reach our common goals.

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