ML Ops Engineer

Job Description

Overview: 
Spotter, named one of TIME100’s Most Influential Companies this year, empowers top YouTube creators to accelerate their business and unleash their full creative potential by giving them access to the capital, knowledge, and community they need to succeed at scale. As the top provider of creator-friendly growth capital, Spotter tailors our investments to meet the unique needs of each creator we partner with, giving them the freedom to create without compromise.
Creators are free to reinvest their funds however they choose, from hiring a team, to building their own production studios, and everything in between, all while maintaining total control over their catalogs, their channels, and their future earnings. In addition to funding, Spotter provides creators with in-depth data insights into the performance of their existing content, enabling them to leverage the full value of their library, as well as the value of future uploads and how they can improve performance in the future.
Featured in Forbes, Fast Company, Variety, Axios, and more, Spotter has already deployed over $850 million to YouTube creators to reinvest in themselves and accelerate their growth. Spotter has licensed content that consists of over 725,000 videos, which generate 88 billion monthly watch-time minutes. With our curated premium video catalog, we deliver a unique scaled media solution to Advertisers and Ad Agencies that is transparent, efficient, and 100% brand safe.What You’ll Do
Join Spotter’s Product team as our first Machine Learning Operations Engineer. This is a pivotal role as we work to scale our state-of-the-art ML models to serve our growing user base. 

Design, build, and maintain scalable solutions for delivering our in-house models across our product.
Enhance the platform’s efficiency and scalability, focusing on GPU resource allocation, data processing, model training, and model deployment.
Collaborate with data scientists, AI engineers, and backend engineers to provide frictionless pipelines for deployment. 
Develop and oversee CI/CD pipelines with ArgoCD and Argo Workflow.
Set up and manage monitoring frameworks using tools like Prometheus and Grafana to ensure the health and performance of our machine learning platform.
Keep up to date on the latest developments in MLOps, distributed computing, and GPUs.

Who You Are

A Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent professional experience.
A minimum of 5 years experience deploying and scaling machine learning models in a production environment.
Extensive experience with CI/CD tools, orchestration platforms (e.g., Airflow, Kubeflow), and containerization (Docker, Kubernetes).
Familiarity with LLMs and diffusion models, especially open-source ones.
Excellent communication skills, capable of collaborating effectively across multiple teams and stakeholders.

Additional Valued Skills

Familiarity with machine learning frameworks such as TensorFlow or PyTorch.
In-depth knowledge of best practices for data governance and security.
Active engagement with the broader machine learning and tech community, keeping up-to-date with industry trends and emerging technologies.

To be considered for this role, please submit your resume along with any relevant certifications or project portfolios that demonstrate your expertise in backend engineering, microservices.
Why Spotter

Medical & vision insurance covered up to 100%
Dental insurance
401(k) matching
Stock options
Complimentary gym access
Autonomy and upward mobility
Diverse, equitable, and inclusive culture, where your voice matters.

In compliance with local law, we are disclosing the compensation, or a range thereof, for roles that will be performed in Culver City. Actual salaries will vary and may be above or below the range based on various factors including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. A reasonable estimate of the current pay range is: $100K-$500K salary per year. The range listed is just one component of Spotter’s total compensation package for employees. Other rewards may include an annual discretionary bonus and equity.Spotter is an equal opportunity employer. Spotter does not discriminate in employment on the basis of race, religion, creed, color, national origin, ancestry, citizenship, physical or mental disability, medical condition, genetic characteristics or information, marital status, sex (including pregnancy, childbirth, breastfeeding, and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, military status, veteran status, use of or request for family or medical leave, political affiliation, or any other status protected under applicable federal, state or local laws. 
Equal access to programs, services and employment is available to all persons. Those applicants requiring reasonable accommodations as part of the application and/or interview process should notify a representative of the Human Resources Department.