Manager, Machine Learning Engineering
Tala · USA
About this role
## Tala — Manager, Machine Learning Engineering ### About Tala Tala is the AI-native credit infrastructure that connects global capital to the global majority. We combine proprietary risk intelligence with a growing network of capital and distribution partners to power credit access at scale. To date, Tala has distributed **$9B+** in capital to **14M+** customers across **Africa, Latin America, and Asia**, building a contextual dataset on thin-file borrowers in emerging markets. Tala is converting that foundation into shared infrastructure that partners, capital providers, and ecosystems can build on. The company has been named to **Fortune Impact 20**, **CNBC’s World’s Top Fintech Companies** (twice), **CNBC Disruptor 50** (for five years), and **Forbes’ Fintech 50** (for ten years running). We’re **remote-first** with office hubs in **Santa Monica, CA (HQ)**, **Nairobi, Kenya**, **Mexico City, Mexico**, **Manila, Philippines**, and **Bangalore, India**. ### The Role Tala is seeking a **Manager, Machine Learning Engineering** to lead the **ML Platform** team. This is a **player-coach** management role. You’ll lead a team of **4–6 Machine Learning Engineers** responsible for building the platforms, frameworks, and infrastructure that enable Data Science teams to **securely train, deploy, monitor, and operate ML models at scale**. A key focus is **real-time ML inference** and **streaming data systems**, along with platforms supporting **batch model development and deployment**. ### What You’ll Do - **Lead & Grow the Team** - Manage and develop a team of **4–6** ML Engineers (mid-to-senior) - **Hire, source, interview, and close** strong MLE talent - Set clear expectations, provide feedback, and create development plans - Coach engineers toward growth/promotion and address performance gaps - Enable engineers to take on challenging projects and build technical leadership - **Own Engineering Delivery** - Set **quarterly goals** and ensure consistent delivery - Own prioritization across product roadmap work, run-the-business, and operational excellence - Balance capacity across new development, maintenance, technical debt, and production support - Improve productivity by reducing context switching and delegating effectively - Partner with engineers/technical leads to estimate and scope complex work - **Provide Technical Leadership** - Guide development of platforms/frameworks for data exploration, feature development, and ML lifecycle (train/test/deploy/monitor) - Lead across **model infrastructure**, **real-time inference**, **streaming feature extraction**, **batch processing**, and **production ML systems** - Drive engineering practices: **testing, automation, observability, fault tolerance, infrastructure-as-code, deployment** - Own and improve **SLOs**, on-call health, capacity planning, reliability, and incident response - Review technical designs and help drive architectural standards and reduce technical debt - **Partner Across the Organization** - Work closely with **Data Science, Data Engineering, Data Platform, Product, Credit, and Business Development** - Translate business/technical needs into scalable ML platform solutions - Coordinate dependencies and delivery across multiple teams - Bring structure and clarity as priorities evolve ### What You’ll Need - **Management Experience** - **2+ years** directly managing engineers (hiring, performance management, coaching, career devel
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