Machine Learning Engineer II

Machine Learning Engineer II

Tala was named one of the top 50 FinTech companies in the world. We are a financial technology company on a mission to make financial services simple, inclusive, and accessible for the doers and dreamers globally.  We are building the digital bank for the next billion!

So far, more than 6 million people in emerging markets have borrowed through our Android app, which provides instant credit scoring, lending, education, and other personalized financial services. Headquartered in Santa Monica, we support the needs of our customers in Kenya, Mexico, Philippines, and India.

The Machine Learning Engineer II will contribute their expertise in both data science and software engineering to develop scalable, robust ML products. This IC role will deliver new products and improvements to our data science infrastructure from within Tala’s Data Platform team, participating in collaborative design discussions and delivering well-tested, performant solutions which meet the quality and design standards of the senior engineering staff. The Machine Learning Engineer II will proactively identify and overcome potential barriers to their project’s success, requesting appropriate guidance and mentorship from senior staff.


    • 2+ years experience working on backend software using modern languages and frameworks (Java, Scala, Python, GoLang)
    • 1+ years of engineering experience relating to data pipelines and machine learning at scale
    • Database experience, relational or non-relational (MySQL, PostgreSQL, Cassandra, HDFS)
    • Some hands-on experience in cloud computing (AWS, EC2, S3, RDS, ELB, GCP, Azure)
    • Some hands-on experience with machine learning tools and tech (such as SageMaker, sklearn)
    • Working knowledge in API development for mobile/web use
    • Ability to build, instrument, and engineer medium to complex projects without excessive reliance on the senior staff
    • Ability to prioritize and communication in a fast paced environment 
    • Ability to clearly communicate and understand algorithms, design, and complex architectures
    • Ability to become quickly proficient with the tools and procedures used by the Data Platform team
    • Readiness to own a task throughout design, development, launch, and post-launch operability
    • Prefer familiarity with Agile development process
    • Prefer experience with batch and real-time processing data (Kafka, Airflow)
    • Prefer advanced degree in Computer Science and/or Math


    • Work closely with Data Scientists to bridge the gap between offline data exploration/model development and scalable, productionized inference tools
    • Assist in the development of a pluggable framework that Data Scientists can use to train, test, and deploy new models according to a self-service principle.Work with Data Science and Data Platform when extensions to this framework are required
    • Collaborate with QA team to make models and model services testable and reliable
    • Build and maintain tooling to monitor deployed models for stability, scalability, and liveness
    • Consult with Data Science as they build tooling to monitor model correctness and drift
    • Collaborate with and support cross functional teams (Product, Data, Credit, and BusinessUnderstand project goals clearly and grasp how they fit into the larger scope of our business
    • Take part in code/design reviews to further develop your sense of code quality, maintainability, test coverage, and good design
    • Continually improve our codebase with clean and efficient code as well as solving problems using the most appropriate technologyConsistently set and meet time expectations for tasks.
About Tala

Our vision is to build a new financial ecosystem where everyone can participate on equal footing and access the tools they need to be financially healthy. We strongly believe that inclusion fosters innovation and we’re proud to have a diverse global team that represents a multitude of backgrounds, cultures, and experience. We hire talented people regardless of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.
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