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Machine Learning Engineer III

Job in Portland, Multnomah County, Oregon, 97204, USA
Listing for: Indeed
Full Time position
Listed on 2026-05-09
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, Software Engineer
Salary/Wage Range or Industry Benchmark: 227000 - 341000 USD Yearly USD 227000.00 341000.00 YEAR
Job Description & How to Apply Below

Our Mission

As the world’s number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and creating the best experience for job seekers.

Day to Day

As a Machine Learning Engineer III, you will be a team lead. You will own one of the team’s major work streams, help drive technical direction for the team, and guide other members of the team to achieve product/technical goals. On a daily basis, you will explore data and formulate problem statements, develop and deploy predictive models while monitoring them in production, and guide the team on the same.

Additionally, you will partner with cross‑functional teams, evangelize your team's work, and stay updated with the latest advancements in the field.

Responsibilities
  • Partner with cross‑functional teams to enhance and optimize search algorithms for improved accuracy, relevance, and overall user experience.
  • Experiment with Proof of Concept Machine Learning model improvements, scale them to production, and run iterative A/B experiments to improve our matching technology while partnering with other teams.
  • Define and clarify project priorities, deliverables, and success criteria in partnership with cross‑functional teams.
  • Act as a bridge between technical and non‑technical collaborators, facilitating effective communication and comprehension of project goals and outcomes.
  • Mentor and grow other software engineers and Machine Learning Engineers across teams.
  • Break down larger Machine Learning initiatives into pieces that deliver incremental business value and guide the team through implementing them.
  • Represent Indeed at major Machine Learning conferences, such as Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the International Conference on Learning Representations (ICLR).
Skills/Competencies
  • Requires a Bachelor’s degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master’s degree with a minimum of 6 years of experience; or a PhD with 3 years experience.
  • Prior success in deploying impactful Machine Learning solutions to large‑scale production systems, while partnering across teams.
  • Solid knowledge of data structures and algorithms.
  • Sense of ownership and accountability as a key contributor in the technical and product domains.
  • Knowledge and practical experience working on Deep Learning Libraries (like Torch, Tensorflow, etc.).
  • Excellent written and verbal communication in English, effective with technical and business audiences.
Salary Range Transparency
  • Tier 1 – United States of America $163,000 – $245,000 USD per year
  • Tier 2 – United States of America $182,000 – $272,000 USD per year
  • Tier 3 – United States of America $199,000 – $299,000 USD per year
  • Tier 4 – N/A
  • Tier 5 – United States of America $227,000 – $341,000 USD per year
Salary Range Disclaimer

The salary range for this role reflects the minimum and maximum compensation for the role. Offers are typically made between the range minimum and the range midpoint. Actual compensation will be determined based on job‑related skills, experience, and expertise, as evaluated during the interview process. The range(s) listed is just one component of Indeed’s total compensation package for employees. Other rewards may include quarterly bonuses, Restricted Stock Units (RSUs), a Paid Time Off policy, and many region‑specific benefits.

Compensation may also vary based on where a role is performed, as work locations are grouped into geographic pay tiers to reflect cost of labor differences in different geographic markets. Candidates can view geographic pay tiers by location on our career site , and recruiters can confirm how location is considered for a specific role.

Benefits – Health, Work/Life Harmony, & Wellbeing

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