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 LATAMMachine 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.
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
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
Required Experience:
At least 4 years experience as a Machine Learning Engineer, Software Engineer, or Data Engineer
4-year Bachelor's degree in Computer Engineering or a related field
Experience deploying data science 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
Experience working with Data Science/Machine Learning software and libraries such as h2o, TensorFlow, Keras, scikit-learn, etc.
Experience with Docker, Kubernetes, or some other containerization technology
Familiarity with multiple data source systems (e.g. JMS, Kafka, RDBMS, DWH, MySQL, Oracle, SAP)
Systems-level knowledge in network/cloud architecture, operating systems (e.g., Linux), storage systems (e.g., AWS, Databricks, Cloudera)
Production experience in core data technologies (e.g. Spark, Pandas)
Development of APIs and web server applications (e.g. Flask, Django, Spring)
Complete software development lifecycle experience including design, documentation, ong analytical abilities; ability to translate business requirements and use cases into a solution, including ingestion of many data sources, ETL processing, data access, and consumption, as well as custom analytics
Excellent communication and presentation skills; previous experience working with internal or external customers
Preferred Experience
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., HBase, Impala, Solr, Kudu, Streamsets, NiFi, ElasticSearch, Databricks, Snowflake, AWS/Azure/GCP)
Relevant side projects (e.g. contributions to an open source technology stack)
AWS Sagemaker, MLFlow experience
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 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.