Join Cantina as a Machine Learning Engineer to lead audio model evaluations and shape the future of social AI.
Posted by employer 6 months ago
First seen on Joblaze 1 month ago
Last verified on the company career page 22 hours ago
Skills & Technologies
AI in the day-to-day
null
Not disclosed in this posting: years of experience, work arrangement, visa sponsorship.
Benefits
Joblaze summary
The Machine Learning Engineer at Cantina focuses on evaluating audio models, particularly in speech generation and recognition, by designing and implementing evaluation pipelines and automated reporting dashboards. Key skills include experience in model training, statistical analysis, and user study design, particularly for large-scale machine learning applications. This role is ideal for a seasoned professional looking to lead an evaluation team and contribute to the growth of innovative AI solutions. As a founding member, the engineer will play a crucial role in shaping the team's direction and impact.
Joblaze insights
- Listed about a month ago — first seen on Joblaze September 3, 2026. Last confirmed on Cantina's careers page October 29, 2026.
- Salary band is in line with the typical range for AI/ML roles (median ~$190,000).
- Starts above 45% of 87 comparable senior ai/ml roles that list Machine Learning we track (median $200,000 across 45 companies). See Machine Learning salary trends
- Machine Learning appears in 17.7% of 1055 comparable senior ai/ml roles; statistical analysis appears in 0.1% of 1055 comparable senior ai/ml roles.
Quick facts
- What's the salary range?
- Cantina lists $200,000–$220,000 for this role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Audio Model Evaluation, Machine Learning, Speech Generation, Speech Recognition, statistical analysis.
- What seniority level is this role?
- Cantina targets senior candidates for this position.
- Is this full-time or contract?
- Full-time for this Machine Learning Engineer, Core Evaluations role at Cantina.
From the original posting
About the Role:
We are seeking an experienced Machine Learning Engineer (MLE) to focus on audio model evaluation, specifically for speech generation and recognition models.
This role involves designing and developing comprehensive model evaluation pipelines for both development and production environments, as well as creating automated dashboards for reporting evaluation results.
As the founding member of our evaluation team, the ideal candidate is expected to leverage their experience to lead our evaluation efforts and play a key role in the future growth of the evaluation team.
What You’ll Do:
Designing model evaluation pipelines for models in development and production
Designing user studies for subjective model evaluations.
Converting requirements into measurable metrics.
Designing and developing automated evaluation dashboard to see model performances and compare results.
Training new models to capture new and different evaluation metrics.
Communicating with the model team to help design better models based on the evaluation results.
Communicating with the data team to help decide the type of data necessary to improve model performance.
Communication with the product-manager to make sure product requirements are correctly measured.
Help grow the evaluation team as the founding member.
Lead the evaluation team in the future.
What You’ll Bring:
Strong experience and intuition for designing metrics that capture model performance.
Strong experience with designing user studies on Mechanical Turk or similar platforms. .
Strong experience with model training and fine-tuning for model evaluation.
Strong statistical knowledge and experience to statistically compare evaluation results and take decisions.
Very strong engineering and programming skills.
Experience with training ASR, TTS models.
Experience at ML teams working on large-scale machine learning problems. (>3B models with >1m hours of data)
Compensation:
When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.
Benefits for U.S.-based roles:
Competitive salary and generous company equity
42 days of paid time off, including:
15 PTO days
10 sick days
15 company holidays
2 floating holidays
Generous parental leave & fertility support
401(k) retirement savings plan
Complimentary lunch and snacks for in-office employees
One Medical membership, and more!
Standard company text repeated across Cantina's postings is omitted here.