Machine Learning Engineer (API Multicloud)

TL;DR

Machine Learning Engineer (API Multicloud): Building and improving AI systems that help strategic partners adapt hirify.global models to cloud-native environments like AWS with an accent on post-training workflows, evaluation, data pipelines, and API integration. Focus on diagnosing failure modes, scaling production ML systems for customization and fine-tuning, and feeding learnings back into the platform for reliability and performance.

Location: San Francisco (onsite)

Salary: $295K – $445K + Offers Equity

Company

hirify.global is an AI research and deployment company dedicated to ensuring general-purpose AI benefits humanity through safe deployment of products.

What you will do

• Partner with customers and teams to define model behaviors, diagnose issues, and translate needs into training and evaluation requirements.
• Build and scale production ML systems for model customization, post-training, and fine-tuning-as-a-service.
• Investigate training workflows, identify improvements in data, evaluation, or infrastructure.
• Integrate ML capabilities into AWS-native API environments with backend and infrastructure engineers.
• Propose improvements to post-training systems, APIs, and developer workflows based on partner learnings.
• Collaborate with Research and Applied teams to productionize model improvements and best practices.

Requirements

• Master’s or PhD in Computer Science, Machine Learning, or equivalent
• 7+ years in ML, infrastructure, or product-driven engineering
• Strong ML engineering in building, training, fine-tuning, evaluating production AI systems with deep learning, transformers, PyTorch/TensorFlow.
• Familiarity with LLM fine-tuning methods like supervised fine-tuning, distillation, preference optimization, RL.
• Strong software engineering in Python/Rust, data structures, algorithms, systems design.
• Experience with model customization, evaluation, data pipelines, distributed systems, cloud infrastructure.

Nice to have

• Experience with AWS, Kubernetes, agents, tool use, runtime environments, AI developer platforms, speech models.

Culture & Benefits

• Operate with high ownership in a fast-evolving 0→1 environment.
• Collaborate across Research, Safety, product, infrastructure, and external partners.
• Equal opportunity employer committed to diversity and reasonable accommodations.
• Background checks per applicable law, considering fair chance ordinances for US-based candidates in SF, LA, CA.