Staff ML Engineer, VoIP Infra — Onsite in SF

Galliot; San Francisco (CA); On-site; USD 160,000 - 220,000; Full time

Benefits offered by this job

Competitive salary

Paid time off

Health benefits

Dental insurance

Employee assistance program

Flexible schedule

Parental leave

Relocation assistance

Retirement plan

Tuition reimbursement

Job summary

Galliot is hiring a Staff Machine Learning Engineer to build intelligent ML capabilities for voice communication infrastructure in an onsite environment in San Francisco.

The ideal candidate will design and deploy ML solutions for VoIP systems, iterate models for voice analytics and optimization, and work closely with infrastructure and software teams to deliver scalable production services.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, ML or related field or equivalent experience
• Extensive experience across machine learning and software engineering
• Strong Python programming and data analysis skills
• Knowledge of VoIP protocols, including SIP and RTP
• Experience deploying scalable production services
• Strong problem-solving abilities and communication skills

Responsibilities

• Design and implement ML solutions tailored to VoIP systems
• Develop and iterate models for voice analytics and communication optimization
• Drive improvements in call quality, latency, and overall system performance
• Collaborate with infrastructure and software engineering teams to integrate ML with production systems
• Deploy, monitor, and maintain production ML systems
• Evaluate model performance and recommend technical improvements based on results

Skills

Python

data analysis

VoIP

SIP

RTP

problem solving

communication

software engineering

machine learning

Education

Bachelor's or Master's in Computer Science or Machine Learning

Tools

Python

SIP

RTP

Job description

Galliot is hiring a Staff Machine Learning Engineer to build intelligent ML capabilities for voice communication infrastructure in an onsite environment in San Francisco.

The ideal candidate will design and deploy ML solutions for VoIP systems, iterate models for voice analytics and optimization, and work closely with infrastructure and software teams to deliver scalable production services.