Software Engineer, Machine Learning

Overview

All potential applicants are encouraged to scroll through and read the complete job description before applying.

As an ML engineer at Substack, you will play a crucial role in developing and implementing cutting-edge machine learning solutions to enhance our product offerings.

You will be part of a dynamic team, collaborating closely with software engineers and data scientists, to bring machine learning models into our codebase and integrate them seamlessly into our products.

This role offers an exciting opportunity to shape the future of our technology stack and make a significant impact.

Substack’s compensation package includes a market-competitive salary, equity for all full-time roles, and exceptional benefits.

Our cash compensation salary range for this role is $185,000 - $240,000. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

Responsibilities

• Lead Substack’s thinking about ML adoption and integration of ML tools and techniques
• Collaborate with cross-functional teams to identify and define machine learning opportunities that align with our product roadmap
• Develop, train, and deploy machine learning models using Python and popular ML frameworks
• Leverage off-the-shelf ML tools and systems to accelerate Substack’s ability to incorporate ML functionality into its product and workflows
• Integrate machine learning models and pipelines into our main JavaScript / TypeScript apps
• Optimize and fine-tune ML models for performance, scalability, and efficiency
• Design and implement data pipelines for data preprocessing, feature engineering, and model training
• Deploy and own integrated product experiences and internal tools

Requirements

• 7+ years of relevant experience with data and ML systems
• Strong programming skills in Python and experience with Python libraries commonly used in machine learning (e.g. Transformers and Tensorflow)
• Solid understanding of machine learning algorithms, deep learning, and statistical modeling
• Independent and autonomous. We’re too small to micromanage, and expect that every person at the company owns their work and can be a leader.
• Hold yourself and others to a high standard when working on production systems.
• Enjoy collaboration with a diverse group of stakeholders while bringing your own unique experience and background to the team

Nice to have

• Proficiency in Node.js and JavaScript for seamless integration of machine learning models into our codebase
• Familiarity with cloud platforms (e.g. AWS or Modal)
• Experience with consumer web applications at scale

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