Key Responsibilities:

• Own the full ML lifecycle: from data ingestion and feature engineering to deployment, monitoring, and iteration.
• Design and develop machine learning, and optimization algorithms to solve business problems, or find suitable solutions through research.
• Champion customer obsession—not just end users, but internal teams who depend on your systems.
• Stay curious: explore new methods, contribute to internal learning, and drive innovation via emerging techniques or tech stacks.
• Lead by example in promoting open communication, earnest feedback, and disagree-and-commit practices.
• Drive improvements across performance, robustness, and maintainability of our ML infrastructure—prioritizing automation, observability, and reliability.
• Act as a technical thought partner to Data Scientists and Product teams, helping bridge experimental models into real-world, high-throughput services.
• Proactively identify pain points, suggest better abstractions, and build tooling that accelerates experimentation and deployment.
• Be responsible for SLIs/SLOs for ML systems, ensure system and model health, monitor data quality, performance and business impact, and devise mitigation plans.

Required Skills & Experience:

• 3+ years of relevant work experience, involved with the application of Machine Learning Engineering to business problems in a commercial environment.
• Willingness to learn and understand complex and multidisciplinary business problems and concepts related to Jabama business operations.
• Deep understanding of the math behind machine learning algorithms and the ability to design and develop new ones.
• A strong command of Scala, Python and SQL, with experience in Go, Java, or other back-end languages being a plus.
• Deep understanding of ML architecture and lifecycle: training, validation, serving, and monitoring.
• Experience working with large-scale data systems and distributed compute frameworks.
• Comfort making trade-offs across latency, performance, and reliability in real-world systems.
• Familiarity with both relational (PostgreSQL, MySQL) and NoSQL (Redis, Elasticsearch, ClickHouse) data stores.
• A pragmatic, delivery-focused mindset—aligned with bias for action and delivering in small, iterative steps.
• A sense of ownership over systems you build—you don’t wait for problems to find you.
• Passion for mentoring, sharing knowledge, and helping others grow.
• Bachelor’s degree or higher in Computer Science, Engineering, or a related field.
• Excellent communication skills in English—clear, direct, and collaborative.