Machine Learning Engineer, Ops
- Role
- AI / ML
- Employment
- Full-time
Open to Anywhere in Europe + US. Set where you work from to check your eligibility.
No BS summary
MLOps engineer for generative audio inference infrastructure, serving TTS, voice conversion, and ASR models. Needs Kubernetes, CI/CD, scalable cloud infrastructure, Python or Go, and GPU inference experience. Remote role limited to the U.S. or Europe.
Core skills
Required skills
Optional skills
About Cantina:
Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.
If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!
About the Role:
We are looking for an MLOps Engineer to build and scale the inference infrastructure for our generative audio models, including Text-to-Speech (TTS), voice conversion, and Automatic Speech Recognition (ASR). You will be responsible for designing and deploying high-performance systems that ensure low-latency, reliable, and scalable model serving for both streaming and batch inference. This role is central to bridging the gap between research and production, ensuring our audio models are optimized for performance and cost-efficiency as we scale.
What You’ll Do:
- Design and maintain inference infrastructure for generative audio model architectures.
- Implement and manage high-performance inference engines.
- Orchestrate service deployments using Kubernetes (K8S), implementing advanced autoscaling paradigms to handle varying traffic loads efficiently.
- Develop and automate robust CI/CD pipelines to streamline the testing and deployment of model artifacts and inference configurations.
- Monitor production systems, establishing observability practices to track latency, resource utilization, and overall model performance.
- Collaborate closely with research teams to optimize model serving paths and evaluate various inference strategies.
- Optimize inference performance for both streaming and batch applications.
What You’ll Bring:
- Deep understanding of modern audio model architectures (e.g., TTS, ASR) and their specific inference requirements.
- Strong hands-on experience with Kubernetes (K8S), container orchestration, and implementing autoscaling strategies for production workloads.
- Solid background in MLOps, including CI/CD automation and managing scalable cloud infrastructure.
- Proficiency in software engineering principles and experience with Python or Go for infrastructure tooling and backend services.
- Experience with GPU-accelerated inference and performance profiling techniques.
- Familiarity with high-performance inference engines (e.g., Triton Inference Server, vLLM-Omni) is a plus.
Compensation:
The anticipated annual base salary range for this role is between $125,000-$165,000 (€110,000-€145,000). 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
- Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
- 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
- Lifestyle spending account – $500/month to use however you’d like
- Complimentary lunch and snacks for in-office employees
- One Medical membership, and more!
What you'll do
- Design and maintain inference infrastructure for generative audio model architectures.
- Implement and manage high-performance inference engines.
- Orchestrate service deployments using Kubernetes, implementing advanced autoscaling paradigms to handle varying traffic loads efficiently.
- Develop and automate robust CI/CD pipelines to streamline the testing and deployment of model artifacts and inference configurations.
- Monitor production systems, establishing observability practices to track latency, resource utilization, and overall model performance.
- Collaborate closely with research teams to optimize model serving paths and evaluate various inference strategies.
- Optimize inference performance for both streaming and batch applications.
What they require
- Deep understanding of modern audio model architectures such as TTS and ASR and their specific inference requirements.
- Strong hands-on experience with Kubernetes, container orchestration, and implementing autoscaling strategies for production workloads.
- Solid background in MLOps, including CI/CD automation and managing scalable cloud infrastructure.
- Proficiency in software engineering principles and experience with Python or Go for infrastructure tooling and backend services.
- Experience with GPU-accelerated inference and performance profiling techniques.
Benefits
- Competitive salary and generous company equity.
- Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina.
- 42 days of paid time off, including 15 PTO days, 10 sick days, 15 company holidays, and 2 floating holidays.
- Generous parental leave and fertility support.
- 401(k) retirement savings plan.
- Lifestyle spending account – $500/month to use however you’d like.
- Complimentary lunch and snacks for in-office employees.
- One Medical membership, and more.
Cantina is a new social platform founded by Sean Parker with an advanced AI character creator. Its bots can interact across voice, video, and text.