Applications Engineer

Location

San Francisco HQ

Employment Type

Full time

Location Type

On-site

Department

R&D

Compensation

• IC4 Estimated salary commensurate with experience. $235K
• Offers Equity
• IC5 Estimated salary commensurate with experience. $258K
• Offers Equity

Tier Guide

Our Compensation Philosophy :

Market-based : Our formula ensures new hires earn at or above current 75th percentile cash compensation benchmarks.

Ownership : Our generous equity program ensures new hires are owners, not just employees.

Transparent : We openly discuss salary expectations to avoid surprises later in the process.

Data-driven : We use objective data to remove bias and ensure consistency in compensation decisions.

About Alembic

Alembic is pioneering a revolution in marketing, proving the true ROI of marketing activities. The Alembic Marketing Intelligence Platform applies sophisticated algorithms and AI models to finally solve this long-standing problem. When you join the Alembic team, you’ll help build the tools that provide unprecedented visibility into how marketing drives revenue, helping a growing list of Fortune 500 companies make more confident, data-driven decisions.

About the Role

We’re looking for a Applications Engineer to support our ML team in transforming experimental ideas into production-grade systems. This is a hands-on development role focused on turning early-stage causal inference models, analytics experiments, and prototypes into stable, maintainable, and performant code.

You’ll work closely with data scientists, product engineers, and platform teams to accelerate the delivery of machine learning capabilities inside Alembic’s product—without needing to be a hard-core ML researcher yourself.

Key Responsibilities

Translate early-stage ML notebooks, proofs-of-concept, and experiments into robust, testable, and modular Python code

Optimize numerical and data-heavy code using Python tools such as Numba, Pandas, and NumPy

Collaborate with ML scientists to improve the reproducibility, efficiency, and maintainability of research workflows

Integrate ML-driven components into larger software systems with clean APIs and versioning practices

Help scale inference pipelines by profiling, parallelizing, or caching performance-sensitive routines

Write documentation and contribute to testing, logging, and monitoring for ML-influenced components

Must-Have Qualifications

4–7 years of software development experience, with a focus on Python and data-centric systems

Strong experience with numerical and analytical Python libraries like Pandas, NumPy, Numba, or SciPy

Ability to work directly with ML prototypes and turn research code into clean, production-quality implementations

Familiarity with software engineering best practices (modular design, testing, version control, etc.)

Clear, structured communication skills and a collaborative mindset when working with researchers and engineers

Nice-to-Have

Interest in causal inference, marketing science, or experimentation platforms

Familiarity with lightweight ML frameworks (e.g., Scikit-learn, XGBoost, LightGBM)

Exposure to APIs and microservices for serving or integrating ML output

What You’ll Get

A high-leverage role in helping bridge the gap between ML research and production systems

The opportunity to shape how Alembic brings ML ideas to life across our platform

Daily collaboration with world-class scientists and engineers

A product-driven team culture that rewards curiosity, clarity, and execution

Compensation Range : $235K - $258K

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