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Manager, Machine Learning Engineering

3 weeks, 3 days ago
United States
Full-time
Lead
Engineering Manager
Software Development
Apache Airflow AWS Azure Cassandra Docker Druid GCP GraphQL gRPC Hugging Face Jupyter Kafka Kubernetes Machine Learning MySQL Pandas PostgreSQL Python PyTorch REST API Scikit-learn Snowflake SQL System Design TensorFlow XGBoost
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Tala

Tala

Tala offers a mobile application that integrates digital and cash financial services, enabling users to manage their credit, savings, and overall financial lives seamlessly in one platform.

Banks
251-1K
Founded 2011
$350M raised
View All Jobs 6

Description

  • Manage and develop a team of 4–6 Machine Learning Engineers.
  • Hire, interview, and close engineering talent while creating career development plans.
  • Set quarterly goals, prioritize roadmap and operational work, and ensure delivery.
  • Balance capacity across new development, maintenance, technical debt, and production support.
  • Guide architecture for ML platforms, real-time inference, streaming features, batch processing, and production systems.
  • Establish practices for testing, automation, observability, fault tolerance, infrastructure-as-code, and deployment.
  • Own SLOs, on-call health, capacity planning, reliability, and incident response.
  • Review technical designs, reduce technical debt, and drive architectural standards.
  • Partner with Data Science, Data Engineering, Data Platform, Product, Credit, and Business Development teams.

Requirements

  • 2+ years of direct engineering management experience, including hiring, coaching, performance management, and career development.
  • Experience managing at least one full performance cycle and supporting promotions and performance improvement.
  • Experience owning team goals, prioritization, estimation, delivery, on-call, incident response, and capacity planning.
  • 6+ years of backend software engineering experience in consumer-scale applications.
  • 3+ years of hands-on Python experience, plus proficiency with SQL.
  • Experience building and operating machine learning or causal inference systems in production.
  • Prior hands-on experience building and deploying ML models or ML infrastructure.
  • Ability to lead architecture and system-design discussions without being the primary coder.
  • Strong understanding of software quality, security, reliability, testing, and production operations.
  • Experience with relevant technologies such as AWS/GCP/Azure, Kubernetes, Docker, Kafka/Kinesis, Airflow/Metaflow, ML frameworks, databases, APIs, and observability tools.

Benefits

  • Remote-first work environment with office hubs in Santa Monica, Nairobi, Mexico City, Manila, and Bangalore.
  • Opportunity to work on financial infrastructure serving customers across Africa, Latin America, and Asia.
  • Inclusive global team representing diverse backgrounds, cultures, and experiences.

Interested in this position?

Apply directly on the company website

Apply Now

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