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Machine Learning Lead

Job in Bellevue, King County, Washington, 98009, USA
Listing for: Compunnel, Inc.
Full Time position
Listed on 2026-06-06
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Job Summary

This role is responsible for designing and developing Machine Learning (ML) solutions to enable intelligent experiences and provide value. The individual will collaborate with business, technology, and product teams to understand product objectives and formulate ML problems, working with minimal guidance.

Key Responsibilities
  • Execute relevant data wrangling activities related to the problem.
  • Conduct ML experiments to understand feasibility and build baseline models to solve business problems.
  • Fine-tune baseline models for optimum performance.
  • Test models internally per acceptance criteria from the business.
  • Identify areas and techniques to optimize models based on test results.
  • Document relevant artifacts for communication with the business.
  • Collaborate with data scientists to deploy models.
  • Work with product teams in planning and execution of new product releases.
  • Set OKRs and success steps for self and team, and provide feedback on goals to team members.
  • Identify metrics for validating models and communicate them in business terms to product teams.
  • Track trends and perform rapid prototyping to understand the feasibility of utilizing new techniques in existing solutions.
Required Qualifications
  • Ability to design and develop ML solutions.
  • Skill in collaborating with business, technology, and product teams.
  • Proficiency in understanding product objectives and formulating ML problems.
  • Experience with data wrangling activities.
  • Capability to conduct ML experiments and build baseline models.
  • Ability to fine-tune models for performance optimization.
  • Experience with internal model testing.
  • Skill in identifying optimization techniques for models.
  • Ability to document project artifacts.
  • Experience working with data scientists on model deployment.
  • Experience working with product teams on product releases.
  • Ability to set OKRs and success steps.
  • Skill in providing feedback to team members.
  • Ability to identify model validation metrics.
  • Proficiency in communicating technical concepts in business terms.
  • Experience with trend tracking and rapid prototyping.
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