Machine Learning Engineer

As a Machine Learning Engineer at Teya in Madrid, your main responsibilities include designing and developing a platform for real-time decision-making to help prevent fraud. You'll build high-quality solutions using tools like Go and Python, collaborate with product managers to create scalable services, and integrate advanced predictive models. Additionally, you'll play a critical role in maintaining engineering excellence through monitoring and observability tools.

To qualify for the Machine Learning Engineer position at Teya, candidates should have at least 2 years of professional experience in software development specifically related to machine learning systems. A solid understanding of data structures, algorithms, and software system design principles is essential. The ability to work independently and collaboratively in a fast-paced environment is also critical.

While specific experience in fraud detection models is not explicitly required for the Machine Learning Engineer role at Teya, familiarity with predictive modeling and risk management systems will certainly give you an edge. A background in developing scalable software solutions and a passion for tackling fraud-related issues will be beneficial.

As a Machine Learning Engineer at Teya, you will primarily work with Go, Python, Kafka, Docker, and Kubernetes. Familiarity with these technologies is crucial as they are integral to building the real-time decision-making platform aimed at fraud detection and mitigation.

Teya offers a competitive benefits package for Machine Learning Engineers including health insurance, 25 days of annual leave plus bank holidays, and flexible working hours. You'll also have the chance to travel to different offices across Europe and enjoy daily office snacks in a friendly and informal environment.

When answering this question, focus on specific projects where you implemented machine learning systems. Discuss the technologies you used and the outcomes of your projects. Make sure to highlight any roles you played in the design and deployment phases as these are crucial for a Machine Learning Engineer position at Teya.

To answer this well, detail your systematic approach to problem-solving, such as breaking down the problem into smaller parts and analyzing them. Provide an example of a specific challenge you faced, how you approached it, and what the outcome was. This demonstrates your analytical and coding skills, essential for a Machine Learning Engineer.

Talk about your collaborative experience in a team setting, emphasizing your role and how you contributed to achieving the project's goals. Highlight communication tools and strategies you used to coordinate with team members and how your collective efforts led to success.

It's important to discuss any hands-on experience you have with Kafka and Docker, detailing specific projects where you utilized these tools. Explain how they helped streamline processes or improve efficiency in the systems you developed.

In your response, discuss various metrics you use for evaluating model performance, such as accuracy, precision, recall, and AUC-ROC curves. Mention any tools or techniques you utilize for model evaluation and improvement.

Discuss your debugging strategies, including how you identify issues at different stages of the machine learning pipeline. You can include techniques like visualizing data distributions, iterating on model parameters, and using logging for deeper insights.

Emphasize your commitment to quality assurance. Share practices such as implementing unit tests, conducting peer reviews, and using monitoring tools post-deployment to ensure the reliability of your machine learning solutions.

Articulate a few challenges such as evolving fraud tactics or data quality issues. Discuss solutions such as adaptive learning algorithms or robust data preprocessing techniques to mitigate these challenges, showing your proactive mindset as a Machine Learning Engineer.

Share your methods for staying current with advancements in the field, like following research papers, attending conferences, participating in online courses, or engaging with professional networks. This demonstrates your passion for continuous learning.

This is a great opportunity to express your alignment with Teya's mission to support small, local businesses. Talk about how your values align with the company's goals, and how your skills can contribute to combating fraud and enhancing the services Teya offers.