Machine Learning Engineer (AI)

Location: San Francisco, United States; on-site

Company

hirify.global builds infrastructure for enterprises to create and orchestrate AI workforces, including autonomous voice- and email-based AI workers.

What you will do

• Design, build, and maintain scalable ML systems covering data ingestion, preprocessing, training, testing, and deployment.
• Develop end-to-end ML pipelines for data collection, labeling, training, validation, monitoring, reliability, and reproducibility.
• Implement MLOps practices including model versioning, experiment tracking, ML CI/CD, and production monitoring.
• Integrate and deploy models into real-time products with a focus on efficiency, scalability, observability, and data quality.
• Collaborate with product and engineering teams while owning the full lifecycle of ML systems.

Requirements

• Strong experience in machine learning, deep learning, and NLP.
• Experience with MLOps, data pipelines, model deployment, production monitoring, and scaling.
• Proficiency in Python and familiarity with Go.
• Experience with ML lifecycle tools such as MLflow, Kubeflow, or Weights & Biases.
• Strong coding, debugging, data engineering, system design, robustness, scalability, and automation skills.
• Ability to work on-site in San Francisco.

Nice to have

• Experience with speech recognition, text-to-speech, or audio processing.
• Familiarity with LLMs, generative AI, or real-time inference systems.
• Experience with Airflow, Prefect, or Dagster.
• Startup experience and familiarity with AWS, GCP, Azure, Docker, or Kubernetes.

Culture & Benefits

• Ownership and autonomy over projects with an expectation of shipping impactful work.
• Healthcare, dental, and vision coverage.
• Competitive salary and equity in a high-growth startup.
• Operating principles emphasize extreme ownership, craftsmanship, focused urgency, first-principles thinking, and friendly collaboration.