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Staff Software Engineer, Machine Learning

Rol remoto de Machine Learning Engineer con fit claro de ubicación del candidato.

Publicado19 jul 2026

Países elegibles1 país aceptado

Señal de senioritySenior

Modelo de trabajoRemoto

Ubicaciones aceptadas para candidatos

Estados Unidos

Resumen del rol

Contenido del rol extraído en secciones para revisar más rápido.

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

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.

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