The Democratic National Committee’s Tech Team is hiring a Machine Learning Engineer responsible for overseeing the end-to-end lifecycle of ML products and maintaining the ML platform. The ML Engineer will embed within the Data Team, a team of data scientists, analytics engineers, data engineers, and data analysts to ship products that will help our users—campaigns and state parties—optimize their voter contact programs. The Tech Team works closely with campaigns up and down the ballot to provide them the tools and data they need to win.

Who we are:

• The Tech Team is a small, diverse team that provides technology, datasets, and data products used by candidates and organizers in all 50 states and in all 3,413 counties across the United States. The Tech Team’s efforts directly give support to analyze data, organize campaigns, define targets, raise money, and get out the vote on Election Day.
• We are building a team geared to take on the biggest challenges. So we are hiring analysts, product managers, engineers, researchers, designers, security experts, IT professionals, client support, and data scientists who can use user-centered design and rapid iteration to develop a rich technology ecosystem for progressives – building tools ourselves as well as partnering with other companies and organizations.

Who you are:

• We're focused on equipping Democratic candidates and campaigns around the country with the data and analytics resources they need to win, and are looking for a Machine Learning Engineer from a diverse range of backgrounds and skill sets. Whether you're new to electoral politics or you've been working with electoral data teams for many cycles, we'd love to talk to you.
• We're looking for candidates who are willing to get nerdy about the details while staying focused on our goal of electing Democrats. Among other things, in this role you could help us:
• Operationalize data science and machine learning workflows. Our end-users rely on our ML products to make decisions every day, so we need to ensure our models are running and performing reliably in production.
• Manage the ML platform. Utilize existing tools, evaluate and integrate new services, or create custom solutions to help data scientists focus on doing data science. Own the end-to-end "experience" for developing and deploying ML models at the DNC.
• Audit and improve our existing data science products and pipelines. Work together with our data scientists and analytics engineers to help us continue building upon and improving our models, the pipelines that produce them, and how we monitor our products in production.
• Develop and deploy new ML products to meet the needs of our users. You will be able to leverage our existing data, identify new data sources to use, experiment with new techniques, evaluate against existing solutions, and productionize the model training and scoring pipelines.
• Identify opportunities to develop new tools and products that help Democrats fully leverage data in their decision-making. Work on better understanding the end users of Democratic data and building the tools that best meet their needs. Help us think about how we can make data, analytics, and data science products more impactful and accessible to the campaigns that rely on them.
• You will be part of the DNC's Data Team and will focus on both 1) the near-term operational efficiency of the DNC, state parties, and candidates and 2) the long-range development of groundbreaking products for the progressive ecosystem at large.

You might be right for this role if you:

• Have a passion for MLOps and designing efficient and scalable ML systems. We'd love to know your opinions and preferences for integrating DevOps and software engineering best practices into data science and machine learning workflows.
• Can work collaboratively within a cross-functional team of product managers, data scientists, and analytics engineers to productionize data and ML products.
• Have experience prototyping, developing, deploying, and monitoring ML models in production settings using:
• Languages such as Python and SQL
• Libraries such as scikit-learn, xgboost, pytorch, pandas, numpy, scipy
• Tools such as Google Cloud Vertex AI, BigQuery ML, dbt, Airflow
• Have experience maintaining ML infrastructure or platform, and utilizing tools/services such as container registries, experiment tracking, feature stores, monitoring and alerting, and pipeline orchestration.
• Have experience assessing the viability of new tools and services in improving our workflows and products, and making build-vs-buy decisions.
• Are interested in exploring state-of-the-art techniques in personalization, recommendations, search, natural language processing, GIS, network analysis, etc and their potential use cases in electoral politics.
• Enjoy the engineering challenge of implementing new methods from academic research to applied real-world settings.
• Have experience doing data science and statistical inference in a social sciences context, which may include electoral politics. In our domain, we spend a lot of time thinking about populations and demographics, and build models using survey data and population estimates.
• Have a user-driven approach to building products, and feel comfortable assessing tradeoffs between developing the best product and shipping a model that will meet user needs.
• Have strong written and verbal communication skills, and experience explaining technical concepts to both technical and non-technical audiences. 
• Are curious, collaborative, humble, eager to learn, and ready to work with a diverse, distributed team to solve interesting problems together!

Do you want to...

• Secure the future of our country? Right now a lot is at stake in our country and our team has a huge opportunity to make a real difference.
• Work with amazing people? We’re building a diverse, distributed team, hiring the best people we can wherever they are—alumni from past Presidential campaigns working out of DC and New York, experienced product developers from the SF Bay Area, and more.
• Never stop learning? There are people who know about politics and people who know about technology and a few who have figured out some things about how to combine the two, but we are blazing a lot of new trails and you should be comfortable exploring and learning from everyone you can.

 The starting salary for the Machine Learning Engineer position is $121,770, on an annualized basis, commensurate with experience and qualifications.

This is a full-time, exempt position, that may require work on weekends, and has an end date of November 15, 2024.  This position is in the bargaining unit represented by SEIU Local-500.

Benefits:

The DNC offers a generous benefit package, including:

- More than 30 days of paid time off, including Federal holidays, open leave, and personal days;

- Health and dental insurance for employee and dependents;

- 90% paid by the DNC, 10% paid by employee;

- Supplementary vision plans available to employees for purchase;

- Pre-tax Flexible spending account benefits available to employees and dependents.