SR Machine Learning Engineer
Ciudad de Mexico Full-time Senior Machine Learning Engineering
At a glance
Senior Machine Learning Engineering role at Pacifica Continental. Ciudad de Mexico · full-time.
Pay not stated Machine Learning Engineer salary
RoleMachine Learning Engineering
SenioritySenior
LocationCiudad de Mexico
EmploymentFull-time
Role brief
aimlroles summary, based on the employer's posting.
What you'll do
- Build and maintain the infrastructure that runs ML models, covering design, deployment, delivery and ongoing monitoring
- Create tools that help the modeling team prepare data, build features, and deploy and serve models
- Improve how models and data science products run, keeping performance and reliability in view
- Structure codebase frameworks and processes so clean coding practices are the default
- Guide engineers and data scientists on sound engineering practices
What you bring
- A bachelor’s degree in computer science, engineering or a related discipline
- At least three years in machine learning engineering, data engineering or a related role, including production code and ML infrastructure
- Strong Python skills and practical knowledge of its libraries and frameworks
- Hands-on feature store experience, plus cloud services such as AWS and data systems for online and offline processing
Who this fits
This senior role suits an engineer focused on ML platforms and tooling, with experience supporting the full model lifecycle and high transaction volumes. You’ll work with engineering, data science, risk, fraud and product teams, and mentor colleagues. Strong English communication and comfort with changing requirements are expected.
From the employer
SR Machine Learning Engineer
As a Machine Learning Engineer, you will play a critical role in developing and maintaining the core systems and infrastructure that power our data science applications. This position is platform/tooling focused.
You will work closely with other engineers, data scientists, risk/fraud analysts and product managers to build, maintain and improve the whole ML platform where our models and other DS products run. You will also develop tools that help our modeling team to create features, train, retrain, deploy, serve and monitor ML models.
In this role, you will own the process of creating and maintaining scalable tools and infrastructure that handle hundreds of millions of transactions per month, ensuring high performance and reliability with a focus on data as a principle. Your work will be instrumental to enhance the impact of the team as it will be a central point of serving both internal and external services.
You will be part of a data science team on a mission to improve access to credit and technology in emerging markets with the opportunity of creating a big and real positive impact to our millions of users across the countries we operate in.
Responsabilites:
Requirements:
As a Machine Learning Engineer, you will play a critical role in developing and maintaining the core systems and infrastructure that power our data science applications. This position is platform/tooling focused.
You will work closely with other engineers, data scientists, risk/fraud analysts and product managers to build, maintain and improve the whole ML platform where our models and other DS products run. You will also develop tools that help our modeling team to create features, train, retrain, deploy, serve and monitor ML models.
In this role, you will own the process of creating and maintaining scalable tools and infrastructure that handle hundreds of millions of transactions per month, ensuring high performance and reliability with a focus on data as a principle. Your work will be instrumental to enhance the impact of the team as it will be a central point of serving both internal and external services.
You will be part of a data science team on a mission to improve access to credit and technology in emerging markets with the opportunity of creating a big and real positive impact to our millions of users across the countries we operate in.
Responsabilites:
- Collaborate with global teams including Risk, Fraud, Engineering and Product to deliver world-class data science products to international markets, including ML models, infrastructure and tools.
- Own the life cycle (design, development, deployment, delivery and monitoring) of the infrastructure that powers our ML models that serve 300 million transactions per month and ensure they have optimal performance.
- Drive the enablement of our modeling team by building new tools or adopting new technologies that will allow them to extract data, generate features and deploy/serve models with ease.
- Work with a data-driven mindset and understand the critical importance of handling data properly and safely.
- Organize frameworks and develop processes in our codebase so that the easy and default coding style is cleanly structured.
- Mentor other engineers and data scientists about best practices in engineering.
Requirements:
- Bachelor’s degree in Computer Science, Engineering, or a related field
- 3+ years of experience as a machine learning engineer, data engineer or a closely related position with a proven track record of writing production-level code and developing and maintaining ML infrastructure.
- Good verbal and written communication skills in English
- Comprehensive knowledge of ML life cycle: from data extraction and feature engineering to model serving and monitoring for live and batch processing.
- High proficiency in Python and a strong understanding of its related libraries and frameworks (e.g., Scikit-Learn, Pandas, Flask, FastAPI, etc).
- Strong background in feature store implementation and usage (Chalk.ai, Tecton, Databricks, Feast, etc.), particularly focused on managing large volumes of data for online and offline processing.
- Demonstrated experience with cloud providers (AWS preferred) and related data services (e.g., databases, storage, serverless computing).
- Ability to work in a fast paced environment with constant requirement changes.