Machine Learning Engineer — United States

About The Company

Triangle Analytics is a startup solving market failures in politics through behavioral intelligence for the stakeholders involved in new infrastructure development. Backed by General Catalyst and Pear VC, the company helps communities, public officials, and developers make better-informed decisions. Today, these groups often rely on fragmented public data, polling, and intuition to understand community priorities and project impacts. Triangle is building systems that model community sentiment, identify the drivers of support or opposition, and help stakeholders find opportunities for shared value. Its platform supports earlier engagement and more informed decisions about outreach, project design, and community benefit frameworks. Triangle’s technology is already deployed in civic use cases across the country, including a $275 million bond project where its models help guide community engagement.

About The Role

Triangle Analytics is seeking a machine learning professional to build and advance the systems that power its core platform. In this role, you will turn fragmented signals about individuals, communities, and stakeholders into reliable behavioral predictions at scale. You will work across applied machine learning research and production engineering, developing modeling approaches while building the pipelines and infrastructure needed to deploy them effectively.

You will collaborate closely with the founders and engineering team and have meaningful ownership of Triangle’s core machine learning architecture. This opportunity is suited to someone who enjoys both experimenting with models and creating robust systems that deliver dependable results in production. Your work will help organizations better understand stakeholder behavior, make decisions with greater clarity, and respond to community needs more effectively.

Qualifications

• Strong proficiency in Python and modern machine learning libraries and tools.

• A strong foundation in machine learning and statistical modeling, including feature engineering, algorithm selection, and evaluation methodology.

• Experience building and productionizing machine learning models.

• Experience with model training, evaluation, inference, and monitoring pipelines.

• Careful attention to detail and a commitment to producing high-quality, concise, consistent, and well-organized code.

• At least three years of industry experience; exceptional early-career candidates will also be considered.

• Familiarity with AWS, GCP, or comparable cloud services is an advantage.

• Knowledge of SQL, databases, large-scale data processing, MLOps, or model-serving infrastructure is beneficial.

• Experience with recommender systems, ranking, personalization, user modeling, transformers, or behavioral prediction is a plus.

• Experience in an early-stage environment, including broad ownership and adapting to evolving requirements, is helpful.

Responsibilities

• Lead the machine learning lifecycle, from model experimentation and development through deployment, scaling, monitoring, and ongoing improvement.

• Build and maintain training, evaluation, and inference pipelines that transform structured and unstructured data into useful behavioral predictions.

• Develop approaches for integrating fragmented data and behavioral signals while supporting reliable model performance at scale.

• Establish standards for model development, deployment, monitoring, evaluation, and iteration.

• Improve the reliability, scalability, and performance of the machine learning systems that power Triangle’s product.

• Make thoughtful tradeoffs among development speed, model quality, system reliability, and engineering complexity.

• Help organizations turn stakeholder intelligence into clearer decisions about resource allocation, engagement priorities, and project planning.

Benefits

The role offers a base salary of $200,000–$265,000, along with material equity compensation. You will have significant ownership of foundational machine learning systems and the opportunity to work closely with the founders and engineering team. Your contributions will support a product with real-world civic applications and help shape how the company develops and scales its core technology.

Equal Opportunity

Triangle Analytics is committed to fair and inclusive hiring. Employment decisions are based on qualifications, experience, and role-related requirements. Candidates are encouraged to apply if their skills and perspective can contribute to the team, even if they do not meet every preferred qualification listed above.