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Machine Learning Engineer

2 months ago

Kitchener, Ontario, Canada CARTA Full time
About Carta

Carta is a leading platform that empowers businesses to manage equity, build innovative products, and invest in the companies of tomorrow. Our mission is to unlock the power of equity ownership for more people in more places.

We are trusted by over 40,000 companies and two million people in nearly 160 countries to manage complex financial data, compensation, and valuations. Our platform supports nearly 7,000 funds and SPVs, representing nearly $130B in assets under administration. We have also facilitated $14B in secondary transactions through our tender offer solutions.

The Role

We are seeking a highly skilled Senior Machine Learning Engineer to join our team. As a key member of our data science team, you will spend a significant portion of your time partnering with domain experts across the company to analyze and explore our proprietary document repository and data set.

Key responsibilities will include:

  • Performing exploratory analyses to understand the dynamics of private markets and ownership from source-of-record documents and systems.
  • Developing large language model (LLM)-powered pipelines to classify complex legal documents and extract key information from these documents to automate onboarding to our suite of products.
  • Developing machine learning models to power new financial products and to extract trends from performance of existing products.
  • Building and deploying containerized prediction services and integrating them with our data pipelines.
  • Partnering with product managers, engineers, designers, and business teams to incorporate ML-generated estimates and benchmarks into products and user-flows.
  • Owning, coordinating, and solving complex, cross-functional problems that extend beyond the traditional boundaries of machine learning.
The Team

Our Machine Learning team is dedicated to powering data products and automation through cutting-edge techniques. We work closely with Carta's core business units and product teams to develop estimation-based data products and large language model (LLM)-powered document intelligence capabilities.

This role is foundational to our team, where you will work with one of the world's most valuable datasets and document repositories. Our models directly enable revenue growth and operational efficiency for the company.

The Impact

You will own significant projects that directly align with the company's strategic initiatives in document intelligence, data products, and data quality. Your contributions will empower leaders across the organization to deliver innovative products, optimize operational efficiency, and make well-informed product decisions.

You will also have the opportunity to develop foundational infrastructure for our team and establish best practices for integrating our machine learning models into production environments. Your work will not only impact Carta's current machine learning capabilities but also pave the way for future engineers, enabling them to build upon your efforts seamlessly.

About You

Candidates must have a strong foundation in statistics and machine learning, be proficient in SQL and Python, and have an analytical mindset. You have a strong bias towards simplicity, are excited by 'zero to one' projects, and can efficiently communicate findings to leadership.

Example traits that we value include:

  • 5+ years of industry experience solving complex data problems with descriptive and predictive statistical models.
  • Proficiency with modern programming languages (Python, R, SQL, etc.) and datastores (Redshift or similar).
  • A deep understanding of modern statistical and machine learning models, when to apply them, and how to evaluate their performance.
  • Experience with large language models (LLMs) and their applications in document intelligence, information extraction, and text classification tasks.
  • Strong written and verbal communication skills, with a particular emphasis on data visualization.
  • A collaborative attitude and a helpful personality.
  • Experience with containerizing ML models and integrating them into production workflows.
  • Experience with building simple ETL pipelines (Airflow or similar) to schedule model training / predictions.