phData

phData

phData specializes in providing comprehensive data engineering, data strategy, and machine learning services, offering end-to-end managed data solutions that facilitate data migrations, integrations, and the development of modern data products and appl...

IT Services
251-1K

Description

  • Design and implement data and machine learning solutions across an evolving technical stack.
  • Recommend the right technologies and solution design for specific use cases from the application layer to infrastructure.
  • Design environments that enable data scientists to build models and work with data.
  • Extract data from customer systems and prepare it for use in analytical environments.
  • Define deployment approaches and infrastructure for machine learning models.
  • Work with data scientists to transform data into actionable insights and deployable machine learning inputs.
  • Partner with data scientists to ensure solutions are deployable at scale and maintainable throughout the lifecycle.
  • Create operational testing strategies and validate models through QA, implementation, testing, and deployment.
  • Ensure the quality of the delivered product.
  • Learn and understand customer technology environments and systems.

Requirements

  • At least 6 years of experience as a Machine Learning Engineer, Software Engineer, or Data Engineer.
  • A 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.
  • Strong working knowledge of SQL, including the ability to write, debug, and optimize distributed SQL queries.
  • Ability to build and operate robust data pipelines across multiple data sources, programming languages, and toolsets.
  • Hands-on experience with big data ecosystem products or languages such as Spark, Snowflake, or Databricks.
  • Familiarity with multiple data sources such as JMS, Kafka, RDBMS, DWH, MySQL, Oracle, or SAP.
  • Systems-level knowledge of network/cloud architecture, operating systems such as Linux, and storage systems such as AWS, Databricks, or Cloudera.
  • Production experience with core data technologies such as Spark, HDFS, Snowflake, Databricks, Redshift, or Amazon EMR.
  • Development experience with APIs and web server applications such as Flask, Django, or Spring.
  • Complete software development lifecycle experience, including design, documentation, implementation, testing, and deployment.
  • Excellent communication and presentation skills with experience working with internal or external customers.
  • A master's or other advanced degree in data science or a related field is preferred.
  • Experience with ecosystem technologies such as Spark, Databricks, Snowflake, or AWS/Azure/GCP is preferred.
  • Relevant side projects or open source contributions are preferred.
  • Experience with machine learning libraries such as h2o, TensorFlow, Keras, or scikit-learn is preferred.
  • Experience with Docker, Kubernetes, or other containerization technologies is preferred.
  • Experience with AWS Sagemaker, Azure ML, or MLflow is preferred.
  • Experience building enterprise ML models is preferred.

Benefits

  • Remote-first work environment.
  • Casual, award-winning small-business work environment.
  • Collaborative culture that prizes autonomy, creativity, and transparency.
  • Competitive compensation and excellent benefits.
  • 4 weeks of PTO plus 10 holidays.
  • Accelerated learning and professional development through advanced training and certifications.

Interested in this position?

Apply directly on the company website

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