Senior Machine Learning Engineer (AI)

Location: Remote - US; additional locations include Chicago, San Francisco, Atlanta, Austin, Boston, Denver, and New York.

Salary: $150K–$250K US base salary annually, determined by work location, skills, experience, education or training, and internal equity.

Company

hirify.global is an AI customer engagement platform for enterprise-scale customer data activation, cross-channel experiences, personalization, and marketing automation.

What you will do

• Build and ship machine learning capabilities for send-time and frequency optimization, recommendation engines, and campaign personalization.
• Own the complete model lifecycle, including EDA, feature engineering, distributed training, deployment, latency monitoring, and online experimentation.
• Build and scale data pipelines and serving architectures with Databricks, Spark, AWS, Ray, and Kubernetes.
• Partner with Backend and Platform teams to improve feature serving, data architecture, and engineering standards.
• Mentor engineers and help define the technical direction for machine learning at hirify.global.

Requirements

• 5+ years of hands-on machine learning engineering experience putting complex models into production at scale.
• Mastery of Databricks and Spark, including building, optimizing, and scaling production data pipelines.
• Experience taking deep learning and ensemble architectures from training and optimization through production deployment.
• Strong Python and/or Scala skills with an emphasis on readable, modular, and maintainable systems code.
• Hands-on experience with microservice backends, distributed compute using Ray or Spark, and Kubernetes containers.
• Pragmatic focus on serving latency, reliability, and measurable customer impact over theoretical novelty.

Nice to have

• Experience with large-scale recommendation systems.
• Experience setting up feature stores or model observability tools.
• Exposure to Infrastructure-as-Code tools such as Terraform or Pulumi.

Culture & Benefits

• Remote work is available for candidates in the US, with additional offices in San Francisco, Denver, London, Sydney, and Lisbon.
• Autonomy spans research, experimentation, production systems, and model ownership.
• Growth is supported through a growth-mindset culture and mentoring opportunities.
• Core values include ownership, growth mindset, collaboration, and transparency.