Lead / Staff - ML Platform / MLOps Engineer

About Aplazo

Aplazo is a Mexican BNPL startup redefining financial access for the underbanked. Unlike its global counterparts, Aplazo isnt just about debtits an alternative to cash, offering fair, simple, and transparent financial solutions. Founded four years ago, Aplazo enables users to split payments online and in-store without a credit card, empowering financial freedom and opportunity across Latin America.

Our tech-driven approach minimizes credit loss while ensuring accessibility—even for the 40% of users with no credit history. With in-store transactions making up more than half of our business, we bridge the gap in Mexico’s evolving financial landscape. Merchants benefit from increased basket sizes, higher conversions, and stronger customer engagement.

$110M in funding

Aplazo on TechCrunch : https://techcrunch.com/2024/05/13/aplazo/

About Data Science @ Aplazo

The Data Science team at Aplazo is a strategic driver of innovation and transformation. With a strong product-first mindset and deep technical expertise, we solve complex problems across risk, payments, personalization, fraud detection, marketing, customer lifecycle, recommendations, underwriting, and more.

MLOps infrastructure

next-generation MLOps capabilities

Role Overview

visionary Lead/Staff MLOps Engineer

Product, Growth, Engineering, and Data

Key Responsibilities

• Architect scalable ML systems

  with a focus on reliability, security, automation, and performance
• Lead the

  end-to-end MLOps strategy

  : CI/CD for ML, model registries, feature stores, testing, deployment, and monitoring
• Drive innovation across ML domains (LLMs, NLP, personalization, fraud detection, pricing, customer science)
  
• Optimize ML workflows for

  cost, latency, reproducibility

  , and resource efficiency
• Define rigorous model governance standards including auditability, reproducibility, versioning, rollback mechanisms
  
• Evaluate and integrate new technologies (LLMOps, Foundation Models, LangChain, etc.) through structured POCs
  
• Serve as

  technical mentor and thought leader

  , influencing teams and instilling engineering excellence
• Partner with executive leadership on quarterly OKRs aligned to risk-adjusted growth, profitability, and model performance
  
• Collaborate across geographies—Mexico, USA, Chile, and Europe—to ensure strategic alignment
  

Required Qualifications

Experience

• 6+ years in MLOps, ML Engineering, or Software Engineering, with 2+ years in a senior leadership role
  
• Proven success in building and scaling production-grade ML platforms
  
• Strong exposure to cloud-native infrastructure (GCP or AWS preferred)
  
• Experience deploying AI/GenAI systems in

  regulated environments

Technical Skills

• Expert in Python

  and ML stack (TensorFlow, PyTorch, Scikit-learn, LangChain, OpenAI APIs)
• CI/CD tools (GitHub Actions, Argo, Kubeflow, MLflow)
  
• Kubernetes, Docker, ONNX, TorchServe for model serving and orchestration
  
• Strong with data warehousing and processing tools (BigQuery, Snowflake, Spark, Kafka, Flink)
  
• Experience with

  metadata management

  ,

  feature stores

  ,

  model versioning

  ,

  A/B testing

  , and

  monitoring systems

• Familiarity with LLMOps, DataOps (Airflow, dbt), and streaming architectures
  

Soft Skills

• Exceptional leadership and mentoring skills
  
• Excellent written and verbal communication
  
• Ability to work independently and cross-functionally in a fast-paced environment
  

Preferred Qualifications

• Bachelor’s or Master’s in Computer Science, Statistics, or related field (Tier-I institutions preferred)
  
• PhD in Data Science, Machine Learning, or related field (with 8+ years of relevant experience)
  
• Publications or conference presentations in ML/AI/DS fields
  
• Spanish language proficiency is a plus
  

Nice to Have

• Experience in fintech, risk, fraud, or payments
  
• Exposure to model fairness, explainability, and responsible AI frameworks
  
• Familiarity with LLMOps stacks (OpenLLM, LangChain, Guardrails) and prompt engineering for GPT-based models
  

Languages

• English:

  Advanced proficiency

• Spanish:

  Nice to have

Why Join Us

• Competitive salary and

  equity

• Remote-first flexibility + in-person offsites
  
• Annual learning budget + global conference participation
  
• Ownership-driven culture, fast iteration cycles, low bureaucracy