Staff Machine Learning Engineer, Virginia

Job Description

A Place for Mom is looking for a Staff Machine Learning Engineer to help build practical, data-driven machine learning applications focused in the Engineering space. In this role, you will develop and deploy scalable ML models that solve business problems within our core product areas.  

This position reports to the VP of Engineering and works directly in the Engineering organization while also working closely with the Data Science team which includes data scientists and machine learning engineers.  

Who you are:

The ideal candidate is self-motivated, goal-oriented, and capable of taking ownership of entire projects.  You proactively identify and recommend areas where your work can make the biggest impact and work across various teams to make that work come to life.  You are experienced in identifying the business value of your work and communicating that value in non-technical terms when needed.  You are comfortable digging into large datasets, using your background in statistics and programming to find patterns and build models that are ready for production while also improving existing algorithms to make them faster, more accurate, and more reliable.

What you will do:

Technical Leadership and Mentoring:Own and drive initiatives from idea to production, managing cross-functional stakeholders.

Drive architecture decisions and influence long-term strategy

Provide ML-specific technical guidance and mentorship to the Engineering Org 

Machine Learning Model Development and Maintenance:Own the full ML lifecycle: from data exploration to model development, deployment, and continuous optimization.

Deep understanding of real-time inference systems, streaming data pipelines, model serving services, feature store monitoring and latency optimization for ML & LLM applications

Solve complex problems with multilayered data sets and optimize existing machine learning libraries and frameworks.

Run machine learning tests and experiments, and document findings and results.

Model Maintenance and Monitoring:Implement and monitor model and data quality checks to ensure accuracy and consistency of our models and pipelines in production.

Train, retrain, and monitor machine learning systems and models as needed.

Collaboration and Support:Collaborate with cross-functional teams, including date engineers, data scientists, machine learning engineers and product managers, to build machine learning applications that align with business objectives and best practices.

Provide support on model and data-related issues and queries from other teams including providing clear and actionable reporting for stakeholders.

Be comfortable working within the Engineering Organization while also using and influencing the ML Platforms and best practices established by the Data Organization.

Best Practices and DocumentationDefine and promote best practices for model implementation, training, evaluation, deployment, monitoring and continuous improvement.