Magnopus

Machine Learning Engineer II

Magnopus$100K — $150K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 4+ years full-time experience in Machine Learning or Data Engineering with a proven track record of delivering ML products
  • Experience in training set creation, model fine-tuning, and ML pipeline operations
  • Strong communication skills for providing direction and feedback
  • Professional experience with live-service platforms/applications

Responsibilities

  • Develop and implement machine learning strategies to improve workflows and content generation
  • Educate teams on machine learning possibilities
  • Build data pipelines for model tuning, training, and deployment
  • Prototype and test machine learning features with cross-functional teams
  • Create internal ML tools to enhance production processes
  • Define and operate solutions including integrations with agentic systems
  • Stay updated on ML and real-time AI trends and ensure scalability

Benefits

  • Collaborative work environment with cross-functional teams
  • Opportunities to work on innovative ML projects that redefine experiences
  • Focus on professional development and skill advancement in emerging technologies
  • Hands-on role that allows for practical application of strategic ML initiatives
Full Job Description
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


$100,000 - $150,000 a year

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