Lead Machine Learning Engineer

Bondora·Remote(Estonia, Latvia, Spain)

AI & Machine Learning

Excel

WFA Digital Insight

As the demand for skilled machine learning engineers continues to soar, with a 25% increase in job postings over the past year, professionals with expertise in building and deploying robust ML infrastructure are in high demand. Bondora's bold vision to expand its lending across more EU countries and broaden its product suite requires a strong technical backbone. With the company poised to acquire a banking license, the need for skilled engineers who can drive the evolution of its ML engineering stack is more pressing than ever. Candidates should be prepared to demonstrate their technical expertise, leadership skills, and ability to innovate and adapt in a rapidly changing environment.

Job Description

About the Role

The Lead Machine Learning Engineer at Bondora will play a pivotal role in driving the company's mission to make finance easy, transparent, and accessible for everyone. As the backbone of the Data Science delivery team, this engineer will be responsible for building and maintaining the robust infrastructure that powers automated model pipelines, ensuring deployment reliability, and governing the full ML lifecycle from experimentation to production. This is a strategic and hands-on engineering role that requires collaboration with cross-functional teams, including Data Science, Data Engineering, and Development, to remove friction, improve scalability, and bring stable, high-quality ML solutions into everyday decision-making. Bondora's ambitious goal of reaching 1 billion in revenue relies on the skills and efforts of its employees, and this role will directly impact the company's growth trajectory and shape the future of its products.

What You Will Do

Guide the technical direction of Bondora's ML engineering stack by selecting, evaluating, and implementing technologies, tools, and processes that improve scalability and reliability.
Lead complex, high-risk, or cross-departmental projects that directly influence Data Science delivery, risk model performance, and production stability.
Act as the bridge between Data Science, Data Engineering, and Development to identify and solve systemic technical challenges.
Design and build advanced, production-grade ML infrastructure and set the engineering standard for the team.
Ensure all ML solutions are secure, observable, resilient, and scalable, following governance, compliance, and operational best practices.
Mentor ML Engineers through code reviews, design sessions, and hands-on technical leadership.
Identify weaknesses or inefficiencies in model or data infrastructure and drive company-wide improvements.
Represent the ML Engineering team in technical discussions and communicate architectural decisions clearly to stakeholders.
Collaborate with the data science team to develop and implement new machine learning models and algorithms.
Develop and maintain technical documentation of the ML infrastructure and models.

What We Are Looking For

Strong Python engineering background and experience with MLflow, Unity Catalog, Databricks, or equivalent platforms used for model lifecycle management.
Proven experience designing ML infrastructure, including CI/CD, containerization with Docker or Kubernetes, and orchestration with Airflow or Prefect.
Deep understanding of monitoring and observability frameworks such as Prometheus, Grafana, or Datadog, and a track record of improving pipeline reliability.
Expertise in model governance, versioning, auditability, and operationalization from research to production.
Solid knowledge of cloud infrastructure on AWS, GCP, or Azure, including cost effectiveness and security best practices.
Experience leading cross-functional initiatives and mentoring engineers.
Ability to balance innovation and stability through structured experimentation, pilot phases, and safe adoption of new technologies.
Strong understanding of data engineering principles and data architecture.
Experience working with large datasets and distributed computing systems.

Nice to Have

Experience with Excel and data visualization tools.
Knowledge of regulatory requirements for financial institutions and experience working in a regulated environment.
Certification in machine learning or data science.
Experience working in an Agile development environment.
Knowledge of cloud-based data platforms and data lakes.

Benefits and Perks

Competitive salary and generous benefits package, including 5 weeks of vacation, private healthcare compensation, hobby grant, mental healthcare support, and share options.
Opportunity to contribute to Bondora's ambitious goal of reaching 1 billion in revenue and shape the future of the company.
Endless opportunities for personal and professional growth in a rapidly evolving and innovative company.
Remote work options with a flexible and autonomous work environment.
Access to cutting-edge technologies and tools.
Collaborative and dynamic team environment with a strong focus on technical excellence.

How to Stand Out

When applying, make sure to highlight your experience with ML infrastructure development and deployment, as well as your ability to lead cross-functional teams.
Showcase your understanding of cloud infrastructure and security best practices, as well as your experience with monitoring and observability frameworks.
Be prepared to discuss your approach to model governance, versioning, and auditability, and how you ensure the scalability and reliability of ML solutions.
Emphasize your ability to balance innovation and stability, and your experience with structured experimentation and pilot phases.
Don't forget to research Bondora's products and services, and be prepared to discuss how your skills and experience align with the company's goals and mission.
Consider including examples of your work, such as code samples or project descriptions, to demonstrate your technical expertise and accomplishments.

This is a remote position listed on WFA Digital, the platform for professionals who work from anywhere. Browse more remote jobs across all categories.