Canadascout
Staff Software Engineer, Machine Learning
Remote Machine Learning Engineer role with clear candidate location fit.
PostedJul 19, 2026
Eligible countries1 accepted country
Seniority signalSenior
Work settingRemote
Accepted candidate locations
USA
Role overview
Staff Software Engineer, Machine Learning
Requirements and responsibilities
Readable role content extracted into sections for faster review.
Key Focuses:
- Design, develop, and maintain advanced machine learning models and algorithms to solve complex business problems
- Lead complex machine learning projects that solve business challenges and add value to the broader ZipRecruiter Business
- Design the overall architecture and infrastructure for machine learning systems, ensuring scalability, efficiency, and robustness
- Push the boundaries of what's possible in machine learning in your organization, finding new and innovative ways to use AI to drive business value
- Provide leadership and set tone for Machine Learning Engineers at ZipRecruiter leveraging industry best practices and innovation
- Stay up-to-date with the latest developments in machine learning and AI, and drive adoption of new techniques and technologies as appropriate
Minimum Qualifications:
- 7+ year of professional software development experience with a deep focus in machine learning
- Comprehensive knowledge and experience of machine learning algorithms, techniques, and best practices
- Extensive experience in machine learning model design, data pipeline design, experimentation and validation design, system design, and/or architecture design.
Preferred Qualifications:
- 10+ year of professional software development experience with an expertise in machine learning
- BS/MS/PhD in Mathematics, Computer Science, Physics, related technical field or equivalent practical experience
- Expert knowledge of machine learning algorithms (e.g., linear regression, SVM, decision trees, neural networks, clustering, etc.) and best practices
- Profound knowledge of machine learning algorithms and frameworks, such as TensorFlow, PyTorch, or scikit-learn
- Extensive background of deep learning architectures and techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM), and Generative Adversarial Networks (GANs)
- Deeply versed in NLP techniques and tools, such as tokenization, stemming, lemmatization, sentiment analysis, and named entity recognition, and libraries like NLTK, SpaCy, or BERT
As part of our team you’ll enjoy:
- Competitive compensation
- Exceptional benefits package
- Flexible Vacation & Paid Time Off
- Employer-matched 401(k) plan
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