Machine Learning Operations Engineer (AI)

TL;DR

Machine Learning Operations Engineer (AI): Owning and scaling production inference systems for a conversation intelligence platform with an accent on high availability, reliability, and efficiency. Focus on building systems for production traffic growth, designing monitoring for ML workloads, and optimizing GPU-based infrastructure.

Location: Hybrid in Somerville, MA

Salary: $150,000 – $200,000

Company

hirify.global is a leader in conversational voice intelligence, building a platform to detect harm and prevent fraud through voice understanding.

What you will do

• Deploy, monitor, and maintain production machine learning inference systems.
• Manage fleets of inference machines to ensure system health and performance.
• Design monitoring, alerting, and incident response systems for ML workloads.
• Build systems and processes for scaling inference infrastructure under variable load.
• Collaborate on infrastructure-as-code for production deployments.
• Support and contribute to GPU-based training and inference infrastructure.

Requirements

• Experience deploying and maintaining production software systems.
• Strong proficiency with AWS, Python, and Linux.
• Experience building monitoring and alerting systems for production environments.
• Exposure to PyTorch or similar ML frameworks.
• Experience working with GPU-based applications and basic GPU tooling.
• Must be based in or able to work hybrid in Somerville, MA

Nice to have

• Experience with ML model serving systems or dedicated model servers.
• Experience monitoring GPU performance for inference workloads.
• Experience optimizing machine learning model inference.
• Familiarity with audio or multimedia data (codecs, streaming, real-time systems).
• Experience with Terraform or CloudFormation.

Culture & Benefits

• Competitive salary and equity.
• Full health, dental, and vision coverage, including HSA and FSA.
• Flexible PTO and a work-from-anywhere policy for up to 8 weeks per year.
• Weekly team lunches and a deeply inclusive, human-centered culture.
• Leadership and technical learning sessions with career development support.