
About Alembic
Transforming marketing insights with AI-driven analytics
Key Highlights
- Raised $169.1 million in Series A funding
- Headquartered in SoMa, San Francisco, CA
- Employs advanced mathematics for marketing attribution
- Analyzes marketing campaigns across multiple channels
Alembic, headquartered in SoMa, San Francisco, CA, specializes in AI-enabled predictive analytics for marketing attribution. The company leverages advanced mathematics and AI techniques, initially developed for pandemic-related research, to analyze marketing effectiveness across channels like TV, ra...
🎁 Benefits
Alembic offers competitive equity options, generous PTO, and a flexible remote work policy to support work-life balance. Employees also benefit from a...
🌟 Culture
Alembic fosters a data-driven culture focused on innovation in marketing analytics. The company values transparency and collaboration, empowering team...
Overview
Alembic is hiring an Applications Engineer to support their ML team in transforming experimental ideas into production-grade systems. You'll work with Python, NumPy, and Pandas to optimize data-heavy code and integrate ML components. This role requires hands-on experience in software development.
Job Description
Who you are
You have a strong background in software development, particularly in Python, and are comfortable translating early-stage machine learning models into robust, testable code. Your experience includes optimizing numerical and data-heavy code using tools like Numba, Pandas, and NumPy, ensuring that the systems you build are both efficient and maintainable.
You thrive in collaborative environments, working closely with data scientists and product engineers to enhance the reproducibility and efficiency of research workflows. Your understanding of APIs and microservices allows you to effectively integrate machine learning outputs into larger software systems, ensuring clean APIs and versioning practices.
You are detail-oriented and have a knack for profiling and parallelizing performance-sensitive routines, helping to scale inference pipelines effectively. Your ability to document your work clearly ensures that your contributions are easily understood and utilized by your team.
What you'll do
In this role, you will be responsible for transforming experimental machine learning notebooks and proofs-of-concept into production-grade systems. You will collaborate with ML scientists to improve the maintainability and efficiency of research workflows, ensuring that the transition from research to production is seamless.
You will optimize data-heavy code using Python tools, focusing on performance and stability. Your work will involve integrating ML-driven components into larger software systems, which will require a solid understanding of clean API design and versioning practices.
You will also help scale inference pipelines by profiling, parallelizing, or caching performance-sensitive routines, ensuring that the systems you build can handle increasing loads efficiently. Your role will be pivotal in bridging the gap between machine learning research and production systems, allowing Alembic to deliver cutting-edge marketing intelligence solutions.
What we offer
Alembic provides a high-leverage role that allows you to shape how machine learning ideas are brought to life across our platform. You will have the opportunity to work daily with world-class scientists and engineers in a product-driven team culture that rewards curiosity, clarity, and execution. We encourage you to apply even if your experience doesn't match every requirement, as we value diverse perspectives and backgrounds.
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