architect, develop, and manage machine learning systems that enable real-time, personalized decision-making across digital and assisted channels.
lead the creation of ML pipelines, online inference services, and decision-time scoring logic.
design and manage end-to-end machine learning systems, including: Feature engineering and reuse strategies, Offline training pipelines, Online inference and scoring services.
ensure systems meet stringent requirements for latency, scalability, reliability, and correctness in real-time contexts.
build and operationalize models such as propensity or likelihood prediction, uplift or incremental impact models, engagement or responsiveness scoring.
collaborate with analytics and product teams to translate business objectives into measurable modeling outcomes.

Requirements

8+ years of experience in machine learning engineering, applied ML, or data-driven platform development
3+ years in a technical lead or senior ML engineering capacity
Deep expertise in: Feature engineering and data pipelines, Model training and evaluation, Real-time or near-real-time inference systems
Strong software engineering skills in Python, Java, or similar languages
Practical experience with AI-assisted development tools to streamline ML workflows.

Benefits

medical, dental and vision benefits
401(k) retirement savings plan
time off (including paid time off, company and personal holidays, volunteer time off, paid parental and caregiver leave)
short-term and long-term disability
life insurance
many other opportunities.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningfeature engineeringdata pipelinesmodel trainingmodel evaluationreal-time inference systemsPythonJavaML pipelinesdecision-time scoring

Soft Skills

leadershipcollaborationcommunication