Senior Machine Learning Engineer

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.

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