Lead / Staff - ML Platform / MLOps Engineer

Job Description

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. Backed by $110M in funding , Aplazo is poised for continued innovation. We’re building Latin America’s most beloved fintech and are seeking passionate technologists and leaders who thrive on collaboration, quality, and impact . 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. A cornerstone of our success is our robust MLOps infrastructure —featuring automated CI/CD pipelines, model and data versioning, and comprehensive observability to support a seamless end-to-end ML lifecycle. Now, we are investing in next-generation MLOps capabilities to further scale and future-proof our systems. Role Overview We are seeking a visionary Lead/Staff MLOps Engineer to lead the evolution of our ML infrastructure. This is a high-impact role for a technical leader who thrives on building scalable platforms, accelerating experimentation workflows, and enabling high-velocity AI development. You’ll define the MLOps roadmap, establish best practices, and build resilient systems that empower our Data Science and Engineering teams to operate at scale. You will work closely with stakeholders across Product, Growth, Engineering, and Data to translate complex business goals into reliable, high-performing machine learning systems. 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