MercadoLibre

2 months ago

Machine Learning Engineer OPs - IT Fintech

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 7 hours agoStatus: Live

Job Summary

Design and scale innovative, secure ML systems in a dynamic, frontier tech environment. Implement MLOps architectures with model serving, data pipelines, and backend services; collaborate with data science teams to productionize models; build interpretable model APIs and pipelines to improve production time, model performance, and cost efficiency.

Location: Bogotá

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Participate in productization of ML models by applying MLOps practices to ensure reliable, reproducible, and sustainable deployments in production environments.
•Collaborate with data science teams to integrate models into the production ecosystem, ensuring compatibility, performance, scalability, and observability.
•Develop and maintain model interpretability architectures by building APIs, backend services, and automated pipelines for deployment and operation.
•Identify and implement technical solutions to automate and optimize ML processes, impacting production time, model performance, and operating costs.
•Contribute to the design and execution of backend services and data pipelines used to serve ML models in production.

Key Requirements

•Must have hands-on experience implementing MLOps architectures, model serving, and platforms with components such as Feature Store or Model Registry across deployment patterns.
•Experience building backend services, data pipelines, and ML models using Python, and integrating tools like BigQuery, Go, and key-value storage systems.
•Experience automating CI/CD processes for ML, applying observability, model monitoring, and interpretability techniques (e.g., SHAP).
•Strong collaboration with data science teams to integrate models into production ecosystems, ensuring compatibility, performance, scalability, security and observability.
•Ability to design and maintain model interpretability architectures, building APIs, backend services, and automated pipelines for deployment and operation.

Experience:FintechIT

Skills:PythonGoBigQueryAPIsMachine learningMLOpsObservabilitySHAPData pipelinesBackend services

Languages:Spanish

Tech Stack:PythonGoBigQueryAPIsSHAPMLOps

Company Brief

MercadoLibre

Operates Latin America's leading e‑commerce marketplace and fintech ecosystem, offering online buying and selling, classifieds, payment processing, credit, and logistics services across multiple countries in the region.

Industry: Online Marketplaces

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Buenos Aires, Argentina

Founded: 1999

Glassdoor: 3.8

Website LinkedIn

Loading job details...

Preparing the role view and application actions.

MercadoLibre

2 months ago

Machine Learning Engineer OPs - IT Fintech

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 7 hours agoStatus: Live

Job Summary

Location: Bogotá

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Participate in productization of ML models by applying MLOps practices to ensure reliable, reproducible, and sustainable deployments in production environments.
•Collaborate with data science teams to integrate models into the production ecosystem, ensuring compatibility, performance, scalability, and observability.
•Develop and maintain model interpretability architectures by building APIs, backend services, and automated pipelines for deployment and operation.
•Identify and implement technical solutions to automate and optimize ML processes, impacting production time, model performance, and operating costs.
•Contribute to the design and execution of backend services and data pipelines used to serve ML models in production.

Key Requirements

•Must have hands-on experience implementing MLOps architectures, model serving, and platforms with components such as Feature Store or Model Registry across deployment patterns.
•Experience building backend services, data pipelines, and ML models using Python, and integrating tools like BigQuery, Go, and key-value storage systems.
•Experience automating CI/CD processes for ML, applying observability, model monitoring, and interpretability techniques (e.g., SHAP).
•Strong collaboration with data science teams to integrate models into production ecosystems, ensuring compatibility, performance, scalability, security and observability.
•Ability to design and maintain model interpretability architectures, building APIs, backend services, and automated pipelines for deployment and operation.

Experience:FintechIT

Skills:PythonGoBigQueryAPIsMachine learningMLOpsObservabilitySHAPData pipelinesBackend services

Languages:Spanish

Tech Stack:PythonGoBigQueryAPIsSHAPMLOps

Company Brief

MercadoLibre

Industry: Online Marketplaces

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Buenos Aires, Argentina

Founded: 1999

Glassdoor: 3.8

Website LinkedIn