TL;DR

Senior Machine Learning Engineer (AI): Building and scaling ML pipelines and production systems that train, evaluate, and serve recommendation models efficiently and at scale with an accent on MLOps, CI/CD for ML, feature stores, model serving, observability, and versioning. Focus on ensuring continuous model performance in a dynamic, global environment, diagnosing and resolving production ML issues.

Location: This role is based in Austin, and we ask that you’re within a commutable distance to this office, so that you’re able to come onsite regularly to collaborate across engineering teams. We have a hybrid environment that requires you to be in the office Monday - Wednesday. Please note: We are unable to offer Visa sponsorship at this time

Salary: $185,000 - $222,500 a year

Company

%hirify_global% Inc. is the parent company of %hirify_global%, Badoo, %hirify_global% For Friends, and Geneva; the %hirify_global% platform enables people to build healthy and equitable relationships, through Kind Connections.

What you will do

Design, build and optimise ML pipelines and production systems that train, evaluate and serve recommendation models efficiently and at scale.
Work in a cross-functional team alongside data scientists, machine learning scientists, software engineers and both technical and non-technical stakeholders.
Partner with ML Scientists to translate research models into efficient, maintainable, and well-tested production systems.
Implement monitoring, observability, and retraining strategies to ensure continuous model performance in a dynamic, global environment.
Contribute to the evolution of our ML infrastructure, including CI/CD, model registries, and feature stores.
Diagnose and resolve production ML issues, such as data inconsistencies and model drift, to identify and resolve infrastructure bottlenecks.

Requirements

5+ years of relevant industry experience.
An advanced degree in Computer Science, Mathematics or a similar quantitative discipline.
Strong software engineering background. You write clean, scalable, and maintainable code in Python or similar languages.
Proven experience deploying and operating ML systems in production environments.
Deep understanding of MLOps and infrastructure concepts: CI/CD for ML, feature stores, model serving, observability, and versioning.
Experience with modern ML frameworks (e.g. PyTorch, TensorFlow) and orchestration tools (e.g. Airflow, Kubeflow, SageMaker, Ray).

Culture & Benefits

Own meaningful projects that directly impact millions of %hirify_global% users.
Learn and grow in a high-performing engineering team committed to mentorship and learning.
Be part of a culture that values respect, excellence, curiosity, courage and joy.
Enjoy competitive compensation, equity, and world-class benefits.