Machine Learning Engineer
Yieldmo is an advertising technology company that operates a smart exchange that differentiates and enhances the value of ad inventory for buyers and sellers. As a leader in contextual analytics, real-time technology, and digital formats, we create, measure, model, and optimize campaigns for unmatched scale and performance. By understanding how each unique impression behaves and looking for patterns and performance in real time, we can drive real performance gains without relying on audience data. What We Need We're looking for a software engineer with a growth mindset to help drive the development and deployment efforts for the data science workflows. You will work on the technical quality, planning, execution, and delivery of all engineering aspects of user stories for the Data Science Team. You must be excited about getting the output of data science work to production, as this role is less about model building and more about the automation and deployment of machine learning and analytics workflows. You should be someone who values code quality and delivering outcomes. You are a highly motivated software engineer with significant experience enabling and scaling data science solutions. You understand how to architect and build reusable components so there is consistency and increased velocity in the development process. You have built data pipelines that are efficient, maintainable, and tunable. You're pragmatic, creative, and know how to get things done with an internal team or with a third-party partner. You understand the tradeoffs between getting things out the door, doing things right, and saying not right now. You can translate complex tasks into elegant and intuitive workflows. You are capable of designing, implementing, and communicating technical solutions to engineers, data scientists, and business stakeholders. While we don't expect you to be an expert in all areas, we do expect that you have enough experience to debug production issues, create technical designs and implement new features. Responsibilities Develop automation pipelines to ingest data and train/deploy models to production Monitor and support data science infrastructure to maintain uptime Architect and implement technical solutions for data science workflows, which are not limited to machine learning, with the goal of putting them in production Develop tools, datasets, and configurable workflows for data scientists Collaborate with product, engineering, and business stakeholders to develop a technical roadmap that enables the data science-driven product roadmap features Setting up and promoting coding best practices, building Python-based reusable frameworks, and performing code reviews Code, debug, test, automate, and support data science workflows Project manage and deliver against our roadmap Collaborate closely with colleagues to deliver complex solutions Ensure cross-team delivery successfully against user stories Work with the product owners on sprint planning, backlog grooming, and generating stories Requirements 5
years experience in machine learning engineering, data engineering, and data science Desire to work with machine learning technologies and toolsets BA/BS or equivalent combination of education and experience Expert-level knowledge of SQL and Python Experience working with large datasets (billions of rows) in high-performance analytics data warehouses such as Snowflake, Redshift, Vertica, or Netezza Team-oriented, with the ability to build relationships and rapport within and across teams Strong verbal and written communication skills In-depth experience with AWS (preferred) or Google Cloud and the ability to leverage cloud services to architect solutions for machine learning and analytics Nice to Haves Ad tech experience Experience building machine learning models in a data scientist capacity Familiarity with Airflow Experience working with Looker data models Experience working with H2O Driverless AI, Google VertexAI, DataRobot, or a similar platform Perks Optional 100% Fully Remote Workplace Generous stipend and white-glove service to help you upgrade your home office 1 Mental Escape (ME) day each month to fully unplug and recharge Work-life balance, flexible PTO, and competitive compensation packages A generous learning stipend and other opportunities for professional development Please note this role is not eligible for placement in Colorado
Salary Range:
$80K -- $100K
Minimum Qualification
Data Science & Machine LearningEstimated Salary: $20 to $28 per hour based on qualifications.
years experience in machine learning engineering, data engineering, and data science Desire to work with machine learning technologies and toolsets BA/BS or equivalent combination of education and experience Expert-level knowledge of SQL and Python Experience working with large datasets (billions of rows) in high-performance analytics data warehouses such as Snowflake, Redshift, Vertica, or Netezza Team-oriented, with the ability to build relationships and rapport within and across teams Strong verbal and written communication skills In-depth experience with AWS (preferred) or Google Cloud and the ability to leverage cloud services to architect solutions for machine learning and analytics Nice to Haves Ad tech experience Experience building machine learning models in a data scientist capacity Familiarity with Airflow Experience working with Looker data models Experience working with H2O Driverless AI, Google VertexAI, DataRobot, or a similar platform Perks Optional 100% Fully Remote Workplace Generous stipend and white-glove service to help you upgrade your home office 1 Mental Escape (ME) day each month to fully unplug and recharge Work-life balance, flexible PTO, and competitive compensation packages A generous learning stipend and other opportunities for professional development Please note this role is not eligible for placement in Colorado
Salary Range:
$80K -- $100K
Minimum Qualification
Data Science & Machine LearningEstimated Salary: $20 to $28 per hour based on qualifications.
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