Manager, Machine Learning

Location: Plano, Texas, United States

Company

hirify.global, including Toyota Financial Services, develops mobility, finance, and insurance solutions with a focus on customer experience and data-driven capabilities.

What you will do

• Hire, coach, and mentor Machine Learning Engineers and senior engineers while building a culture of ownership and continuous improvement.
• Set technical direction for architecture, testing, deployment, observability, drift detection, revalidation, data quality, and production readiness.
• Partner with data science, analytics, data engineering, product, risk, finance, and technology teams to turn business priorities into technical plans.
• Oversee high-throughput services, batch pipelines, optimization and operations research engines, and analytics applications on AWS, Snowflake, or comparable platforms.
• Own the ML engineering roadmap, portfolio delivery, prioritization, technical debt, and operating model across multiple business domains.
• Improve MLOps practices through reusable patterns, CI/CD, automated testing, monitoring, alerting, reproducibility checks, and incident response.

Requirements

• Master’s degree in Computer Science, Engineering, Data Science, Statistics, Mathematics, Operations Research, or a related technical field, or equivalent practical experience.
• At least 7 years of professional experience in data science, machine learning engineering, or applied ML, including ownership of production systems.
• At least 2 years of people-management experience or equivalent technical-team leadership experience.
• Experience building, deploying, and operating machine learning or optimization systems through design, monitoring, drift management, and retraining in the cloud.
• Strong Python and SQL skills, with experience using AWS, GCP, or Azure and technologies such as Snowflake, Spark, or Databricks.
• Must have the right to work in the United States and must not require current or future Toyota immigration support or visa sponsorship.

Nice to have

• PhD in a quantitative or technical discipline.
• Experience with regulated decisioning in lending, insurance, fraud, risk, or pricing.
• Advanced MLOps experience with Docker, Kubernetes, infrastructure as code, model registries, drift detection, data validation, or deployment governance.
• Generative AI experience, including LLM workflows, RAG, semantic search, evaluation, guardrails, monitoring, or responsible AI.
• AWS machine learning, solutions architecture, developer, or equivalent certification.

Culture & Benefits

• Collaborative, respectful, flexible work environment focused on teamwork and inclusion.
• Professional growth programs and tuition reimbursement.
• Comprehensive health care and wellness plans, paid holidays, and paid time off.
• 401(k) plan with company matching and an annual retirement contribution, where applicable.
• Vehicle purchase and lease programs, family support referral services, and tax-advantaged accounts.