Manager, Machine Learning Engineering

🕒 September 17

🇺🇸 United States – Remote

💵 $170k - $210k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 1%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Tala

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2011

💳 Fintech

🤖 Artificial Intelligence

👥 B2C

Fintech • Artificial Intelligence • B2C

Tala is a fintech company that aims to break down financial barriers for individuals across Kenya, Mexico, the Philippines, and India through its innovative money app. The company provides a suite of financial services, including credit, payments, savings, and transfers, to empower their customers. Leveraging advanced artificial intelligence and machine learning technologies, Tala offers personalized financial experiences and creates digital financial identities for users who have been underserved by traditional finance institutions. With a focus on real-time money management, Tala's app simplifies access to instant credit and other financial services for millions, enhancing users' economic power and quality of life.

📋 Description

• Lead Tala’s ML Platform team • Manage and develop a team of 4–6 Machine Learning Engineers across mid-to-senior levels • Hire, source, interview, and close strong MLE talent • Establish expectations, provide feedback, and create development plans • Coach engineers toward growth and promotion while addressing performance gaps • Set quarterly goals and ensure consistent delivery • Own prioritization across product roadmap work, run-the-business activities, 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 and technical leads to estimate and scope complex work • Guide development of platforms and frameworks for data exploration, feature development, and ML model training, testing, deployment, and monitoring • Provide technical leadership across model infrastructure, real-time inference, streaming feature extraction, batch processing, and production ML systems • Drive testing, automation, observability, fault tolerance, infrastructure-as-code, and deployment practices • Own and improve SLOs, on-call health, capacity planning, reliability, and incident response • Review technical designs and drive architectural standards and technical debt reduction • Collaborate with Data Science, Data Engineering, Data Platform, Product, Credit, and Business Development teams • Translate business and technical needs into scalable ML platform solutions • Coordinate dependencies and delivery across engineering and data teams

🎯 Requirements

• 2+ years of directly managing engineers, including hiring, performance management, coaching, and career development • Experience managing a team through at least one full performance cycle • Demonstrated ability to coach engineers toward promotion and address underperformance effectively • Experience owning team goals, prioritization, estimation, and delivery • Experience with production on-call, incident response, and capacity planning • Willingness to be actively involved in sourcing, interviewing, and closing engineering talent • 6+ years of backend software engineering experience in consumer-scale applications • At least 3 years of hands-on Python experience • Experience building and operating machine learning or causal inference systems in production • Earlier-career experience personally building and deploying ML models or ML infrastructure • Ability to participate in technical architecture and system-design discussions and provide technical direction without needing to be the primary coder • Strong understanding of software quality, security, reliability, testing, and production operations • Experience with Python and SQL • Experience with machine learning technologies including Jupyter, Pandas, Scikit-Learn, XGBoost, TensorFlow, PyTorch, and Hugging Face • Experience with AWS, GCP, Azure, Kubernetes, and Docker • Experience with streaming technologies including Kafka, Kinesis, Beam, Flink, and Spark Streaming • Experience with batch processing technologies including Airflow and Metaflow • Experience with databases including MySQL, PostgreSQL, Cassandra, Snowflake, and Druid or similar technologies • Experience with REST, GraphQL, gRPC, and Protocol Buffers • Experience with DevOps, SLOs, monitoring/observability, on-call, capacity planning, and root-cause analysis • Experience with scalable algorithms and causal inference

🏖️ Benefits

• Remote-first work approach • Office hubs in Santa Monica, CA; Nairobi, Kenya; Mexico City, Mexico; Manila, the Philippines; and Bangalore, India • Diverse and inclusive global team environment