Senior Machine Learning Engineer at Tala

  • Anywhere
  • Applications have closed
  • Anywhere
  • Applications have closed

Website Tala

Senior Machine Learning Engineer


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. More than 5 million people in emerging markets have borrowed through our smartphone 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 Senior Machine Learning Engineer will architect and stabilize Tala’s core machine learning models and services, using their expertise in both data science and software engineering to deliver scalable, robust ML products. This IC role will work to define and deliver new products and improvements relating to data science at Tala from within the Data Platform team, participating in collaborative design discussions and delivering well-tested, performant solutions which are reliable and trusted by the senior engineering staff. The Senior Machine Learning Engineer values the craftsmanship of clean and efficient code, believes in solving complex challenges with the most appropriate technologies, and helps to set standards and best practices for data engineering as a whole. The Senior Machine Learning Engineer will proactively identify and address potential barriers to success, both individually and for the team, and take ownership of their solutions.
What you will do:

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.
Assist QA team in making 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.
Mentor engineers, data scientists, and analysts on best practices and code efficiency.
Review design documents, perform code reviews, and weigh in on implementation choices from other technical teams.
Collaborate with and support cross functional teams (Product, Data, Credit, and Business Development) to ship solutions that align to our overall business strategy.
Continually improve our codebase with clean and efficient code as well as solving problems using the most appropriate technology

What you will need:

4+ years experience working on backend software using modern languages and frameworks (Java, Scala, Python, GoLang)
4+ years of engineering experience relating to data pipelines and machine learning at scale
Hands-on experience with machine learning tools and tech (such as SageMaker, sklearn)
Strong database experience, both relational and non-relational (MySQL, PostgreSQL, Cassandra, HDFS)
Strong hands-on experience in cloud computing (AWS, EC2, S3, RDS, ELB, GCP, Azure)
Experience with batch and real-time processing data (Kafka, Airflow)
Working knowledge in API development for mobile/web use
Strong collaboration experience with Data Science and Analytics teams
Excellent ability to prioritize and communication in a fast paced environment
Proficiency in Agile development process
Degree in Computer Science and/or Math
Fluent in English and Spanish

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