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Machine Learning Engineer

Job in Aliso Viejo, Orange County, California, 92656, USA
Listing for: Compunnel, Inc.
Full Time position
Listed on 2026-06-05
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 100000 - 130000 USD Yearly USD 100000.00 130000.00 YEAR
Job Description & How to Apply Below

Job Summary

The ML Engineer II will design and develop ML models that deliver accurate results to solve identified business problems using state‑of‑the‑art techniques under the guidance of Senior ML Engineers. This role involves collaborating with cross‑functional teams to build valuable ML solutions for products.

Key Responsibilities
  • Work with cross‑functional teams (business, technology, product) to understand product vision and build ML solutions that bring value to the product.
  • Execute data wrangling activities to create viable datasets for ML problems.
  • Conduct ML experiments to assess feasibility and build baseline models.
  • Fine‑tune baseline models for optimum performance.
  • Test models internally against business acceptance criteria.
  • Identify areas and techniques for model optimization based on test results.
  • Document relevant artifacts for business communication.
  • Collaborate with data scientists on model deployment.
  • Work with product teams in planning and execution of new product releases.
  • Set OKRs and success steps, and provide feedback on goals for team members.
Required Qualifications
  • Ability to design and develop ML models to solve business problems using state‑of‑the‑art techniques under guidance.
  • Experience working with cross‑functional teams including business, technology, and product.
  • Proficiency in data wrangling activities to create viable datasets.
  • Experience conducting ML experiments to understand feasibility and build baseline models.
  • Experience fine‑tuning models for optimum performance.
  • Experience testing models internally per acceptance criteria.
  • Ability to identify areas and techniques for model optimization.
  • Experience documenting relevant artifacts for business communication.
  • Experience collaborating with data scientists for model deployment.
  • Experience working with product teams in planning and execution.
  • Experience setting OKRs and success steps, and providing feedback on team goals.
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