At Shara, we’re building for a future where African banking is free, frictionless, and driven by user experience, where banks are an enabler of the economy, not a tax on it. Where bankers no longer get away with mopping up deposits of the masses to lend to the few. We believe this future of banking is inevitable, and we want to be the first to build it.

We’re an all-in team of people across Kenya, Nigeria, and the US, looking for peers to join us. We care about results, not hours logged. If you’re more comfortable in a Nairobi market or Lagos bus stop than a big corporate office and want to work with switched-on product, engineering, and finance teams building for millions of underserved African SMEs and consumers, we’d love to chat with you. If you’re a no-drama, roll up your sleeves, and hop on a flight tomorrow; a customer-driven person who can build from day one, we can’t wait for you to join us.

About this role

We’re looking for a highly qualified and experienced Machine Learning Software Engineer to join our Data Science team and help build and deploy the machine learning models and infrastructure that will be at the core of the cloud-native banking future we are building. Your development work will support and bring this vision to life, as we develop data-enabled and analytics-driven banking products to serve our markets best. As a core member of our Data Science team, you will have the opportunity to design, deploy, and maintain the foundational machine learning infrastructure that will make all of this happen, as well as help to grow the group with future machine learning engineers and data scientists.

In this role, you will:

• Architect and build machine learning pipelines to bring models from development to production
• Deploy machine learning models onto our GCP infrastructure using the latest best practices
• Build and deploy models on a Kubernetes cluster, working with our DevOps team to fit within our company wide infrastructure
• Develop and maintain RESTful APIs and a Feature Store
• Write & maintain well-tested and documented code.
• Take a high level of ownership and responsibility for your work.
• Work closely with cross-functional stakeholders such as Data Scientists, Products Managers, Engineers, and others to successfully execute and deliver features.
• Make tradeoffs considering business priorities, user experience, and a sustainable technical foundation.

What you bring to the table

• Strong technical experience, with 3+ years of hands-on experience building and maintaining machine learning models, machine learning operations, and machine learning pipelines
• Knowledge of FastAPI and other Python API development frameworks with the ability to translate models from development into highly available APIs
• You’ll work mainly in Python and SQL, but we care more about general engineering expertise and problem-solving than specific language knowledge.
• Strong interest in data and modern data infrastructure technologies such as Big Query, DBT, Airbyte, Dagster, Weights & Biases, Great Expectations, Feast, and other machine learning experiment and development platforms.
• Familiarity with the full cycle of software development, from design and implementation to testing and deployment.
• Excellent communication skills and the ability to articulate complex, technical concepts to any audience.

Nice to haves

• Experience building fintech or banking applications.
• Experience supporting Machine Learning Infrastructure.
• Experience optimizing end-to-end performance of distributed systems.

Our Stack

• Python, SQL, FastAPI
• Java, NodeJS, React Native.
• Postgres, MySQL, BigQuery.
• Kafka, CircleCI, GCP, AWS, Kubernetes, Docker, Firebase, FireStore
• Datadog, Sentry.