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Machine Learning Engineer IV, Data
Remote Machine Learning Engineer role with clear candidate location fit.
PostedJul 4, 2026
Eligible countriesWorldwide
Seniority signalSenior
Work settingRemote
Accepted candidate locations
Worldwide
Role overview
Machine Learning Engineer IV, Data
Requirements and responsibilities
Readable role content extracted into sections for faster review.
Who we are:
- Multiple medical plans including a high deductible, low cost health plan
- Company-sponsored (paid) Short-Term Disability, Long-Term Disability, and Life Insurance
- Comprehensive optional benefits such as Dental, Vision, Supplemental Life/AD&D, Legal/ID Protection, and Accident and Critical Illness Insurance
- Generous paid time off options, including uncapped vacation days, the greater of 3 paid sick days or in accordance with the applicable state or local paid sick leave law, 6 paid company holidays, 2 floating holidays, parental leave, bereavement leave, jury duty leave, voting leave, and other forms of paid leave as required by applicable law or regulation
- Employee Stock Purchase Program with additional opportunities to earn stock in the Company
- Retirement planning through the Company’s 401(k)
The core responsibilities of this role are:
- Design and train high-performance computer vision models for automated damage detection, focusing on precision, recall, and model robustness.
- Architect and maintain high-throughput, containerized microservices for model serving using REST/gRPC to ensure low-latency performance.
- Collaborate with business stakeholders to translate complex inspection requirements into scalable, production-grade ML solutions.
- Own the end-to-end model lifecycle, from experimentation and design to deployment and optimization in high-traffic environments.
- Design and maintain robust data pipelines using Kafka to ensure high-fidelity inputs for model serving and inference.
Required Qualifications:
- Graduate education (MS or PhD) in a computationally intensive domain or equivalent work experience.
- 5+ years of prior computer vision experience
- Advanced proficiency with Computer Vision frameworks (e.g., PyTorch, OpenCV, TensorFlow) and Python/SQL.
- Experience designing and maintaining visual data annotation pipelines and evaluation frameworks for complex, real-world image datasets.
- Experience optimizing high-latency models for real-time inference
- Backend software engineering experience in the cloud (AWS / GCP) with a focus on microservices (docker) and the ML model development lifecycle.
- Experience building and maintaining streaming data pipelines (e.g., Kafka) for real-time model serving.
Preferred Qualifications:
- Knowledge of ML frameworks and libraries, such as Kubeflow, Databricks, KServe and so on
- Experience designing evaluation frameworks for complex visual data
- Experience leading technical design reviews
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Location eligibility
This role is listed as open to candidates worldwide.
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