Machine Learning Engineer II

Posted Yesterday
Los Angeles, CA, USA
Hybrid
100K-150K Annually
Mid level
Digital Media • Information Technology
The Role
The Machine Learning Engineer II will develop ML strategies, build and implement ML pipelines, educate teams, and create internal tools for production workflows.
Summary Generated by Built In

Magnopus is looking for a Machine Learning Engineer who thrives at the intersection of product innovation, real-time systems, and creative collaboration. In this role, you won’t just build models, you’ll help define how machine learning transforms our projects and unlocks entirely new experiences.

You’ll partner closely with product, project, engineering, and creative teams to identify high-impact opportunities for ML, rapidly prototype solutions, and bring them into production at scale. This is a hands-on role where strategic thinking meets deep technical execution.

Responsibilities

  • Work with teams and projects to develop and implement a machine learning (ML) strategy to enhance our workflows and content generation capabilities.
  • Educate the team on what is possible with ML. 
  • Build pipelines and prepare data for tuning, training, and deployment of models optimized for targeted inference. 
  • Partner with teams to prototype and test ML-powered features. 
  • Develop internal tools using ML to streamline workflows for production, art, animation, or audio pipelines. 
  • Define, deploy, and operate agentic solutions, including integrations with MCP servers, tool definitions, and swarms of agents.
  • Create agent friendly interfaces for our tools and processes.
  • Implement models and pipelines from academic publications.
  • Remain current with ML and real-time AI trends and ensure performance scalability across platforms.

Required Qualifications

  • 4+ years full time work experience in Machine Learning, Data Engineering or related quantitative field with a track record of delivering end-to-end ML products
  • Experience building training sets, fine tuning models, building agentic systems and building and operating ML pipelines
  • Strong communication skills, and able to give clear direction and provide constructive feedback
  • Professional experience working on live-service platforms/applications

Nice to Haves

  • Experience with near real-time inference systems in games or interactive applications
  • Familiarity with generative AI (e.g., text, image, audio, or animation models)
  • Background in game development or creative tooling
  • Experience optimizing models for performance on constrained hardware (mobile, console, etc.)
  • Knowledge of MLOps best practices, including CI/CD for ML systems
  • Experience implementing solutions contemplated in academic publications

Skills Required

  • 4+ years full time work experience in Machine Learning, Data Engineering or related quantitative field
  • Experience building training sets, fine tuning models, building agentic systems and operating ML pipelines
  • Strong communication skills to provide direction and feedback
  • Professional experience working on live-service platforms/applications
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The Company
Los Angeles, California
217 Employees
Year Founded: 2013

What We Do

Experience Engineers uniting the physical & digital. Using #spatialcomputing, #AI, & #cloudtech, we imagine, create, & execute impactful immersive solutions. Located in the US and UK, we are empowered by an Academy Award-winning team of designers, artists, engineers, and "get it done"​ producers who bring a diverse body of experience and creative solutions to the field. Our unique focus on story and content-driven technology development gives us advance access to some of our partner's over-the-horizon hardware and software developments in light field technology, holographic and translucent displays, HMDs, performance capture, and new human computing interfaces. We're honored to have a diverse team of talented individuals building products and experiences that have a positive impact on people's everyday lives, whether in entertainment, education, industry, or government

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