• Scale ML innovation by building tools, infrastructure, and workflows that dramatically improve the speed and reliability of model development. • Work backward from modeling needs to design systems that directly unlock gains in accuracy, efficiency, and scientific productivity. • Explore new algorithms and methodologies for our machine learning models and develop tooling to support them. • Improve the entire ML lifecycle—from data readiness and feature development through training, evaluation, serving, and monitoring. • Automate and standardize operational workflows, enabling scientists to focus on high-leverage modeling and analysis rather than manual pipelines. • Define the roadmap for our next generation ML Platform, balancing near-term impact with long-term architectural scalability. • Collaborate cross-functionally with Data Engineering, ML Platform, Pricing, and other teams to build reliable, end-to-end ML systems.

• przestrzeganie dobrych praktyk tworzenia oprogramowania oraz dbanie o ich aktualność, we współpracy z zespołem seniorów ds. uczenia maszynowego, • wspieranie lidera projektowego oraz przełożonego w inicjatywach związanych z Machine Learning, • dążenie do przestrzegania firmowych standardów i kierunków rozwoju w obszarze uczenia maszynowego, • zaangażowanie w procesy analityczne i doradcze, związane z wdrażaniem rozwiązań opartych na AI, • zaangażowanie w proces presale, • monitorowanie trendów rynkowych oraz dostosowywanie rozwiązań względem wymagań biznesowych, • udzielanie wsparcia merytorycznego w ramach strategicznych działań wewnątrz firmy.

• Bridge research and production, building AI models and agent systems that ship into real products. • Architect, evaluate, and optimize autonomous voice and digital agents powering 10M+ customer interactions per month across West Africa. • Build for the hardest edge cases: poor connectivity, low literacy, and languages with little training data. • Experiment with, evaluate, and integrate the latest voice and text models. • Own problems end-to-end, from problem discovery to running in production, working alongside product and engineering leaders who prioritize shipping real customer impact.

• Design and construct Ikue's AI Studio in collaboration with Product owners and Data Scientists • Design and build machine learning pipelines (model build, evaluation, deploy, monitoring) • Integrate machine learning outputs into real-time and batch data pipelines • Ensure machine learning and data pipelines are monitored, reliable and supportable (including expert support when required)