Machine Learning Solutions Architect

phData; Ciudad de México; A distancia; MXN 1.716.444 - 2.231.377; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive compensation

Generous PTO

Collaborative culture

Descripción de la vacante

A data solutions company is seeking a Machine Learning Engineer to design and implement data solutions. You will facilitate the development of machine learning models, ensuring they meet performance and operational standards. The ideal candidate has extensive experience in software engineering, particularly in Python and Scala. This remote-first role values diversity, creativity, and collaboration, offering excellent benefits and a casual work environment.

Formación

• At least 6 years experience in Machine Learning Engineering or related field.
• Experience deploying machine learning models in a production setting.
• Strong working knowledge of SQL.

Responsabilidades

• Design and create environments for data scientists.
• Extract data from customer systems for analytics.
• Ensure model deployment and operational integrity.

Conocimientos

Machine Learning Engineering

Python

Java

Scala

SQL

Data Pipeline Development

API Development

Cloud Architecture

Educación

Bachelor's degree in Computer Science or related field

Herramientas

Spark

Snowflake

Databricks

AWS

Docker

Kubernetes

Descripción del empleo

Join phData, a dynamic and innovative leader in the modern data stack. We partner with major cloud data platforms like Snowflake, AWS, Azure, GCP, Fivetran, Pinecone, Glean, and dbt to deliver cutting‑edge services and solutions. We're committed to helping global enterprises overcome their toughest data challenges.

phData is a remote‑first global company with employees based in the United States, Latin America, and India. We celebrate the culture of each of our team members and foster a community of technological curiosity, ownership, and trust. Even though we're growing extremely fast, we maintain a casual, exciting work environment. We hire top performers and allow you the autonomy to deliver results.

• 6x Snowflake Partner of the Year (2020, 2021, 2022, 2023, 2024, 2025)
• Fivetran, dbt, Atlation, and AWS Partner of the Year
• #1 Partner in Snowflake Advanced Certifications
• 600+ Expert Cloud Certifications (Sigma, AWS, Azure, Dataiku, etc)

Recognized as an award‑winning workplace in the US, India, and LATAM.

Machine Learning Engineers are the Swiss army knives of machine learning. They’re ready for anything, and they bring all the tools to ensure that data science models see the light of day. They own the infrastructure and deployment plan—from making sure data science models can actually be built using customer data to deploying them into a production environment, and everything in between. They provide thought leadership by recommending the right technologies and solutions for a given use case, from the application layer to infrastructure. Machine Learning Engineers have the team leadership and coding skills (e.g. Python, Java, and Scala) to get their solutions into production and to help ensure performance, security, scalability, and robust data integration.

As a Solutions Architect on our Machine Learning Engineering team, you are responsible for:

• Designing and implementing data solutions best suited to deliver on our customer needs — from model inference, retraining, monitoring, and beyond — across an evolving technical stack.
• Providing thought leadership by recommending the technologies and solution design for a given use case, from the application layer to infrastructure; and leading teams with coding skills (e.g. Python, Java, and Scala) to build and operate in production; and to help ensure performance, security, scalability, and robust data integration.

What you’ll do in this role:

• Design and create environments for data scientists to build models and manipulate data.
• Work within customer systems to extract data and place it within an analytical environment.
• Learn and understand customer technology environments and systems.
• Define the deployment approach and infrastructure for models and be responsible for ensuring that businesses can use the models we develop.
• Demonstrate the business value of data by working with data scientists to manipulate and transform data into actionable insights.
• Reveal the true value of data by working with data scientists to manipulate and transform data into appropriate formats in order to deploy actionable machine learning models.
• Partner with data scientists to ensure solution deployability—at scale, in harmony with existing business systems and pipelines, and such that the solution can be maintained throughout its life cycle.
• Create operational testing strategies, validate and test the model in QA, and implementation, testing, and deployment.
• Ensure the quality of the delivered product.

This job might be for you if you bring:

• At least 6 years experience as a Machine Learning Engineer, Software Engineer, or Data Engineer.
• 4‑year Bachelor's degree in Computer Science or a related field.
• Experience deploying machine learning models in a production setting.
• Expertise in Python, Scala, Java, or another modern programming language.
• The ability to build and operate robust data pipelines using a variety of data sources, programming languages, and toolsets.
• Strong working knowledge of SQL and the ability to write, debug, and optimize distributed SQL queries.
• Hands‑on experience in one or more big data ecosystem products/languages such as Spark, Snowflake, Databricks, etc.
• Familiarity with multiple data sources (e.g. JMS, Kafka, RDBMS, DWH, MySQL, Oracle, SAP).
• Systems‑level knowledge in network/cloud architecture, operating systems (e.g., Linux), and storage systems (e.g., AWS, Databricks, Cloudera).
• Production experience in core data technologies (e.g. Spark, HDFS, Snowflake, Databricks, Redshift, & Amazon EMR).
• Development of APIs and web server applications (e.g. Flask, Django, Spring).
• Complete software development lifecycle experience, including design, documentation, implementation, testing, and deployment.
• Excellent communication and presentation skills; previous experience working with internal or external customers.

You might also have:

• A Master’s or other advanced degree in data science or a related field.
• Hands‑on experience with one or more ecosystem technologies (e.g., Spark, Databricks, Snowflake, AWS/Azure/GCP).
• Relevant side projects (e.g. contributions to an open source technology stack).
• Experience working with Data‑Science and Machine‑Learning software and libraries such as h2o, TensorFlow, Keras, scikit‑learn, etc.
• Experience with Docker, Kubernetes, or some other containerization technology.
• AWS Sagemaker (or Azure ML) and MLflow experience.
• Experience building enterprise ML models.

Why phData? We offer:

• Remote‑First Work Environment.
• Casual, award‑winning small‑business work environment.
• Collaborative culture that prizes autonomy, creativity, and transparency.
• Competitive comp, excellent benefits, generous weeks PTO plus 10 Holidays (and other cool perks).
• Accelerated learning and professional development through advanced training and certifications.

phData celebrates diversity and is committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at phData. We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at People Operations.