Senior Machine Learning Engineer

About the Role

Senior Machine Learning Engineer

Our client is a global data intelligence company that transforms large-scale real-world data into reliable, actionable insights for high-impact use cases. The organization operates at the intersection of data engineering, machine learning, and modern AI systems, enabling data-driven decision-making at scale.

The company is currently at a key stage of technological evolution, focused on scaling production-grade machine learning systems, incorporating modern AI and agentic architectures, and strengthening the reliability, automation, and observability of its data platforms, with direct impact on product and business outcomes.

What will you do in this role?

As a Senior Machine Learning Engineer, you will take on a hands-on, senior technical role with strong ownership.

Your mission will be to design, build, and operate production Machine Learning systems, working with large-scale geospatial datasets and ensuring that models, pipelines, and agentic workflows run in a reliable, scalable, and automated manner.

We are counting on your expertise to:

• Design, build, and maintain large-scale geospatial data pipelines capable of processing millions or billions of records.
• Build, deploy, and monitor ML/AI models in production (batch) with a strong focus on quality, performance, and reliability.
• Implement and integrate agent-based systems into real operational workflows.
• Develop backend services and ML tooling that enable other teams to consume models and data products efficiently.
• Establish end-to-end observability for pipelines, models, and agents, including metrics, alerting, and tracing.
• Optimize distributed systems while balancing performance, cost, and scalability.
• Collaborate closely with product and business teams, translating real-world needs into technical solutions that drive measurable value.

What should you bring to the role?

• Advanced English, both speaking and writing.
• Proven experience as a senior Machine Learning Engineer, with production ML systems running at scale.
• Strong background in distributed data processing using tools such as Spark, Python, and Scala.
• Hands-on experience designing and operating end-to-end ML systems (data ingestion, training, deployment, monitoring).
• Solid experience working with cloud infrastructure, particularly across data, compute, and ML services.
• Practical knowledge of CI/CD pipelines, infrastructure as code, and containerization.
• Ability to work autonomously with a high level of technical judgment and ownership.
• Experience collaborating effectively with both technical and non-technical stakeholders in remote, cross-functional environments.

Desired competencies

• Strong engineering mindset, focused on building robust systems rather than isolated models.
• Structured thinking and ability to solve complex, ambiguous problems.
• High analytical capability and sound technical decision-making.
• Strong focus on reliability, scalability, and long-term maintainability.
• Clear and effective communication with diverse stakeholders.
• Proactive attitude and strong sense of responsibility for the systems you build and operate.

What will you gain from this role?

• A high-impact senior technical role with real ownership over critical machine learning systems.
• The opportunity to work with massive datasets and modern AI technologies in production environments.
• Direct exposure to product and business teams, with tangible impact on outcomes.
• An international, remote-first environment with highly skilled technical peers.
• The opportunity to continue building a strong, long-term technical career in large-scale Machine Learning and data systems.

Submit your resume and join a process that can change your life.

Best regards,

T-mapp Team