ML Engineer

Apollo Agriculture is the commercial farming platform that helps small-scale farmers maximize their profits. Apollo’s ML-powered credit models and automated operations technology unlock the massive, untapped small-scale farming market, starting in Kenya. With optimized financing, high-quality farm products, and digital advice, Apollo farmers are already more than doubling their farm profitability. Apollo’s team brings together technology, credit and operations experience from The Climate Corporation (acquired for USD $1 Billion), Google, Capital One and One Acre Fund. We value evangelical pursuit of mission with a pragmatic approach, humility in the face of challenge, active discussion of disagreements, and considerate listening. 
About the Role:Apollo is seeking an experienced Machine Learning Engineer to help take our analytics capabilities to the next level. While being in the Data Science team, you will be working closely with colleagues in the Engineering team. If you are an experienced machine learning engineer and would like to start working closer with data scientists, then this is a good opportunity!Your

Responsibilities:

• Identify and help develop in-house microservices. These will be largely Python packages
• Be involved in model development from an early stage to future-proof for production
• Establish a model baseline, address concept drift, and prototype how to develop, deploy, and continuously monitor/improve a productionized machine learning application
• Build data pipelines by gathering, cleaning, and validating datasets. Establish data lifecycle by using data lineage and provenance metadata tools.
• Contribute to establishing best practices in coding and repository management

You Are:

• Have strong technical skills regarding data analysis, statistics, machine learning and programming
• Able to start with a simple algorithm, identify time and space complexities, and then modify it to work efficiently at scale
• Experience with building and maintaining productionized machine learning models in Python
• Experience with building and maintaining durable in-house solutions that support data scientists and apply best practices and delivery techniques 
• Are comfortable in challenging established ways of working
• Can communicate technical concepts to non-technical peers
• Analytically rigorous but opts for simplicity where possible
• Excited to spend time with business domain experts and our customers to learn from them
• Able to not only code in Python, but also maintain and refactor existing Python codebases
• Have experience with cloud platforms (GCP, AWS, Azure etc.)
• Have familiarity with coding in SQL, Scala and Java

We are:

• Are a collaborative team of smart and ambitious people who are dedicated to serving our customers.
• Make magic happen to solve hard problems and always come with solutions when challenges arise.
• Are comfortable taking risks that can result in radical scale, and understand that failures are opportunities to learn and improve. 
• Are considerate listeners and take the time to deeply understand and seek out ideas from the people around us, even when we disagree. 
• Offer a dynamic environment that fosters talent, collaboration and growth.
• Take pride in our work and share the responsibility to see it through from conception to deployment. 
• Back up our talk with a competitive compensation and benefits package and challenging projects. 
• Value autonomy, honesty, transparency, and respect.
• Are excited to hear from you!

Nothing in life is perfect, including this job description. You may well be an excellent candidate even if you don’t meet all of the qualifications.