Machine Learning Engineer

Clara; México; A distancia; USD 60,000 - 100,000; Jornada completa

Descripción de la vacante

An innovative company is seeking a skilled Machine Learning Engineer to join their dynamic Data Team. In this role, you will design and maintain complex ML systems, develop data pipelines, and ensure high-quality model deployment. This position offers a unique opportunity to work with cutting-edge technologies and collaborate with talented professionals across LATAM. If you are passionate about shaping the future of business finances in Latin America and thrive in a fast-paced environment, this role is perfect for you. Join a team that values clarity, simplicity, and inclusivity, and make a significant impact in the B2B payments landscape.

Servicios

Competitive salary

Stock ownership plan

Adaptable benefits

Opportunities for growth

Formación

• 4+ years of experience in ML model deployment and infrastructure.
• Proficiency in Python and SQL with strong ML algorithm knowledge.

Responsabilidades

• Develop and maintain ML data pipelines ensuring reliability and scalability.
• Collaborate with data scientists to implement and monitor ML models.

Conocimientos

Python

SQL

ML Algorithms

CI/CD tools

GitHub Actions

Data Quality Monitoring

Distributed Systems

Data Pipeline Development

AWS Services

Big Data Technologies

Herramientas

Apache Airflow

AWS Glue

AWS Sagemaker

Databricks

MLflow

Descripción del empleo

Clara is the leading spend management platform for companies in Latin America. Our end-to-end solution includes locally-issued corporate cards, bill pay, and our highly-rated software platform; already being used by thousands of the most successful companies across the region.

Clara is backed by top investors and strategics including Accial Capital, Canary, Citi Ventures, Coatue, DST Global, General Catalyst, Goldman Sachs, ICONIQ Growth, Kaszek, Monashees, and Notable Capital, as well as prominent angel investors.

Disclaimer: This role is open to all candidates across LATAM, not just the posting location.

CLARA's Data Team is looking for a highly professional and experienced Machine Learning (ML) Engineer to join us and take an active role in the ML-data architectural design alongside our teams of data engineers and data scientists to create, deploy and maintain complex ML systems and services.

Your primary focus will be to develop data pipelines for ML, design, implement and deploy the ML models and infrastructure, improve existing processes, and create data models. You will also be responsible for the maintenance and operation of all these models and data pipelines, and collaborate with other teams to provide high-quality and fast-delivery ML models for the company.

The main challenges and responsibilities you will face are:

• Build, integrate and maintain ML feature data pipelines following reliability, scalability, and maintainability principles.
• Deploy, monitor, and operate ML model lifecycle (ML Ops).
• Collaborate with data scientists in the implementation of ML models.
• Ensuring and monitoring the data quality, and understanding/resolving any issue detected.
• Consume data from Data Vaults and Star Schema lakehouse.
• Be able to collaborate with teams remotely, not only locally.
• Stay up to date with the latest technologies and look for ways to implement them.
• Document your work to have a solid foundation for new team members or future references.
• Code review and peer programming activities.
• Enforce team best practices and DevOps as a culture within the team.
• Enforce Data Security and Data Privacy best practices.

Our requirements for this position are:

• 4 years of experience in Model deployment and infrastructure.
• Proficiency in Python and SQL.
• ML Algorithms experience, both theoretical and practical.
• Experience with CI/CD tools (GitHub Actions, GitLab CI, Jenkins, etc.).
• Experience using Github flow.
• Experience implementing the feature store paradigm.
• Experience deploying streaming ML models with common ML frameworks (e.g. xgboost, scikit-learn, catboost).
• High-level understanding of Distributed Systems and Spark Architecture.
• Experience integrating data from Databases, APIs, and Event Streams (kinesis, kafka).
• Experience developing complex data pipelines (ETL/ELT) with orchestration tools (e.g. Apache Airflow, AWS Glue Workflow, AWS Step Functions, etc.)
• Experience with AWS services: Redshift, Glue, Sagemaker, Lambda, Athena, S3, Kinesis, or other cloud equivalent services.
• Experience with big data technologies and frameworks (e.g. (py)Spark, Scala, Hive, Kafka, etc.)

Nice to have:

• Databricks platform usage and administration
• MLflow

The way we do things is as important as what we do. That is why we operate on a set of carefully-identified values. They are what we expect from ourselves and each other in our day-to-day.

We value:

*Clarity- Open and direct communication

*Simplicity- Pare things down to the essential

*Ownership- We're all owners and act like it

*Pride- Make quality products we're proud of

*Inclusivity- Every voice counts; we value each other for our shared mission and contributions

We are:

* Shaping business finances in Latin America

* Driven by our 6 core values

* Proud of our inclusive and caring culture

* Certified as Top LinkedIn Startup

What We offer:

* Competitive salary & a robust stock ownership plan

* A set of benefits that are adaptable to your needs & way of life

* Opportunities for growth in a fast-paced environment

* A chance to shape B2B payments in Latin America and increase the region’s economic competitiveness

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