LocationSan Francisco HQEmployment TypeFull timeLocation TypeOn-siteDepartmentR&DCompensationIC4Estimated salary commensurate with experience. $235K • Offers EquityIC5Estimated salary commensurate with experience. $258K • Offers EquityTier GuideOur 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 AlembicAlembic 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 RoleWe’re looking for a Machine Learning 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 ResponsibilitiesTranslate early-stage ML notebooks, proofs-of-concept, and experiments into robust, testable, and modular Python codeOptimize numerical and data-heavy code using Python tools such as Numba, Pandas, and NumPyCollaborate with ML scientists to improve the reproducibility, efficiency, and maintainability of research workflowsIntegrate ML-driven components into larger software systems with clean APIs and versioning practicesHelp scale inference pipelines by profiling, parallelizing, or caching performance-sensitive routinesWrite documentation and contribute to testing, logging, and monitoring for ML-influenced componentsMust-Have Qualifications4–7 years of software development experience, with a focus on Python and data-centric systemsStrong experience with numerical and analytical Python libraries like Pandas, NumPy, Numba, or SciPyAbility to work directly with ML prototypes and turn research code into clean, production-quality implementationsFamiliarity with software engineering best practices (modular design, testing, version control, etc.)Clear, structured communication skills and a collaborative mindset when working with researchers and engineersNice-to-HaveInterest in causal inference, marketing science, or experimentation platformsFamiliarity with lightweight ML frameworks (e.g., Scikit-learn, XGBoost, LightGBM)Exposure to APIs and microservices for serving or integrating ML outputWhat You’ll GetA high-leverage role in helping bridge the gap between ML research and production systemsThe opportunity to shape how Alembic brings ML ideas to life across our platformDaily collaboration with world-class scientists and engineersA product-driven team culture that rewards curiosity, clarity, and executionCompensation Range: $235K - $258K #J-18808-Ljbffr