Senior Machine Learning Engineer

• Execute software engineering tasks to support end-to-end machine learning operations, with a focus on scaling workflows for large data and distributed systems.

• Design, build, and maintain MLOps systems, including microservices, queuing systems, APIs, and orchestration workflows using Python, Kubernetes, Kafka, and modern database systems.

• Implement observability tools such as Prometheus and Grafana to ensure reliability, performance, and visibility of ML systems in production.

• Collaborate closely with data scientists and machine learning engineers to streamline workflows for LLM, generative AI, and Agentic AI development and deployment.

• Review architecture and implementation plans to ensure alignment with organizational goals, scalability, and best practices.

• Mentor junior and mid-level engineers, fostering a culture of collaboration, innovation, and operational excellence.

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.

• 5+ years of professional experience in Machine Learning, MLOps, DevOps, or Software Engineering, with a focus on building scalable and reliable software systems.

Core Technical Expertise

• Proficiency in Python and Linux, with strong knowledge of designing scalable, distributed systems.

• Hands-on experience in designing, implementing, and maintaining MLOps workflows, including CI/CD pipelines, monitoring, and production optimization.

• Strong background in cloud computing (AWS/GCP), infrastructure as code (Terraform), containerization, and orchestration (Kubernetes).

• Solid understanding of modern software development practices such as test-driven development (TDD), systems thinking, and CI/CD automation.

Observability & Reliability

• Experience deploying and managing observability tools such as Prometheus, Grafana, and OpenTelemetry to ensure high reliability and performance in production ML systems.

• Expertise in scaling and optimizing distributed systems for large-scale, multi-node computations.

Collaboration & Leadership

• Proven ability to collaborate effectively with cross-functional teams, supporting data scientists and ML engineers in deploying and scaling ML models, including LLMs and generative AI systems.

• Demonstrated capability in leading technical projects, mentoring junior and mid-level engineers, and fostering a culture of collaboration, innovation, and operational excellence.

Professional Attributes

• Pragmatic approach: delivering efficient, real-world solutions while maintaining technical excellence.

• Strong attention to detail with a focus on precision and robustness in system design and implementation.

• Accountability for deliverables, adherence to company standards, and commitment to ethical guidelines.

What we offer: 

• Medical care
• Sport Card (MultiSport)
• MultiLife (mental and physical wellbeing)
• Attractive employee referral program
• Nearmap subscription (naturally)