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Model Server Assistant Jobs in San Ramon, CA (NOW HIRING)

Sesame

ML Model Serving Engineer

San Francisco, CA · On-site

Experience working on high-performance server systems--you'd be just as comfortable with the ... Sesame is a voice tech startup focused on developing AI voice assistants that create natural and ...

Burma Inc

Assistant General Manager

San Francisco, CA · On-site

$85K - $90K/yr

Model and enforce exceptional customer service practices * Address and resolve guests' complaints ... Communicate effectively with kitchen staff, servers and management * Ensure alignment of team goals ...

Burma Inc

Assistant General Manager

San Francisco, CA · On-site

$85K - $90K/yr

Model and enforce exceptional customer service practices * Address and resolve guests' complaints ... Communicate effectively with kitchen staff, servers and management * Ensure alignment of team goals ...

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How much do model server assistant jobs pay per hour?

As of Jul 28, 2026, the average hourly pay for model server assistant in San Ramon, CA is $15.00, according to ZipRecruiter salary data. Most workers in this role earn between $10.77 and $16.92 per hour, depending on experience, location, and employer.

Can you make $100,000 as a server?

A Model Server Assistant typically earns hourly wages that are below $100,000 annually, as this role is often part-time or entry-level. Achieving a $100,000 salary generally requires advanced skills, experience, or working in high-end or specialized environments, which are uncommon for this position.

Can you make good money as a server assistant?

As a server assistant, earnings typically come from an hourly wage plus tips, with total income varying based on location, establishment, and shift hours. While some may earn a modest income, tips can significantly increase overall pay, especially in busy or high-end restaurants. Experience and efficiency can also impact earning potential in this role.

What does a server assistant do?

A server assistant supports restaurant staff by greeting guests, setting tables, refilling drinks, and ensuring cleanliness. They help maintain smooth service flow and may assist with basic food delivery or cleaning tasks. Good communication skills and attention to detail are important for this role.

What are the key skills and qualifications needed to thrive as a Model Server Assistant, and why are they important?

To thrive as a Model Server Assistant, you need a strong understanding of machine learning models, server deployment, and basic programming skills, usually supported by a degree in computer science or a related field. Familiarity with tools like Docker, TensorFlow Serving, Kubernetes, and cloud platforms is typically required. Attention to detail, effective communication, and problem-solving abilities help set candidates apart in this role. These skills ensure efficient deployment, reliable model performance, and smooth collaboration between data science and engineering teams.

What jobs pay 4000 a week without a degree?

A Model Server Assistant role typically does not pay $4,000 a week without a degree; such high earnings are uncommon in this field. Generally, jobs that can pay this amount without a degree include specialized sales, certain skilled trades, or entrepreneurial ventures, often requiring experience, certifications, or specific skills. High-paying roles without a degree are rare and usually involve performance-based pay or commission structures.

How does a Model Server Assistant typically collaborate with data scientists and engineers on machine learning projects?

As a Model Server Assistant, you will work closely with data scientists to ensure machine learning models are properly deployed, monitored, and maintained in production environments. Your responsibilities often include updating model versions, troubleshooting deployment issues, and optimizing server performance. You’ll also collaborate with engineers to integrate models into existing systems and automate workflows, making strong communication and teamwork skills essential. This cross-functional collaboration not only helps you learn from experienced professionals but also opens up opportunities for growth into more specialized roles in machine learning operations.

What is the difference between Model Server Assistant vs Model Trainer?

AspectModel Server AssistantModel Trainer
CredentialsTypically requires basic technical certifications or training in AI/ML support rolesOften requires advanced degrees or certifications in machine learning or data science
Work EnvironmentSupports model deployment and server management in data centers or cloud environmentsFocuses on developing and training models in labs or development environments
Employer & IndustryTech companies, AI service providers, cloud platformsResearch institutions, AI startups, tech firms

The Model Server Assistant primarily supports the deployment and maintenance of AI models on servers, ensuring smooth operation. In contrast, the Model Trainer focuses on developing and training models from scratch. While both roles require technical knowledge, the Model Server Assistant emphasizes support and management, whereas the Model Trainer emphasizes development and experimentation.

What are Model Server Assistants?

Model Server Assistants are specialized software tools or agents designed to help manage, deploy, and maintain machine learning models on server infrastructure. They facilitate tasks such as model versioning, scaling, monitoring, and providing APIs for real-time inference. By automating these processes, Model Server Assistants make it easier for organizations to integrate machine learning models into production environments and ensure they run efficiently and reliably.
What cities near San Ramon, CA are hiring for Model Server Assistant jobs? Cities near San Ramon, CA with the most Model Server Assistant job openings:
Model Server Assistant jobs near you
ML Model Serving Engineer

ML Model Serving Engineer

Sesame

San Francisco, CA • On-site

Full-time

Posted 11 days ago

Job description

Job Summary:
Sesame is a company focused on creating lifelike computers that can see, hear, and collaborate with humans. They are seeking an ML Model Serving Engineer to enhance their serving layer with various LLM, speech, and vision models, while collaborating with infrastructure and training engineers to optimize performance and reliability.
Responsibilities:
• Turbocharge our serving layer, consisting of a variety of LLM, speech, and vision models.
• Partner with ML infrastructure and training engineers to build a fast, cost-effective, accurate, and reliable serving layer to power a new consumer product category.
• Modify and extend LLM serving frameworks like VLLM and SGLang to take advantage of the latest techniques in high-performance model serving.
• Work with the training team to identify opportunities to produce faster models without sacrificing quality.
• Use techniques like in-flight batching, caching, and custom kernels to speed up inference.
• Find ways to reduce model initialization times without sacrificing quality.
Qualifications:
Required:
• Expert in some differentiable array computing framework, preferably PyTorch.
• Expert in optimizing machine learning models for serving reliably at high throughput, with low latency.
• Significant systems programming experience; ex. Experience working on high-performance server systems—you’d be just as comfortable with the internals of VLLM as you would with a complex PyTorch codebase.
• Significant performance engineering experience; ex. Bottleneck analysis in high-scale server systems or profiling low-level systems code.
• Always up to date on the latest techniques for model serving optimization.
Preferred:
• Familiarity with high-performance LLM serving; ex. experience with VLLM, SGlang deployment, and internals.
• Experience with a public cloud platform such as GCP, AWS, or Azure.
• Experience deploying and scaling inference workloads in the cloud using Kubernetes, Ray, etc.
• You like to ship and have a track record of leading complex multi-month projects without assistance.
• You’re excited to learn new things and work in a multitude of roles.
Company:
Sesame is a voice tech startup focused on developing AI voice assistants that create natural and emotionally resonant conversations. Founded in 2022, the company is headquartered in San Francisco, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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