Z
ZipRecruiter
Senior Software Engineer (Machine Learning)
Skills
Deep LearningPyTorchTensorFlowMachine LearningNLP / Natural Language Processing
2 months ago
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Important information
Contract type:
Permanent
Salary:
$140,000 – $200,000 / year
Location:
Santa Monica, CA, USA
Work mode:
Onsite
Published on:
29 August 2026
What they need
- Here, your experience will be put to work crafting new, data-driven features that impact the lives of millions, connecting them to their dream jobs
- We’re tackling exciting challenges: imagine developing a system that can predict salaries for new job postings, using a training set of job postings and known salaries
- But the fun doesn’t stop at model-building
- Our work involves an immersive dive into data - gathering, cleaning, analyzing, and extracting meaningful insights
- This role will design, develop, and maintain machine learning models and algorithms to solve complex business problems
- Identify patterns, trends, and anomalies in the data, and visualize insights using appropriate tools
- Assess the performance of machine learning models using appropriate metrics, validation techniques, and testing datasets
- Discover opportunities to optimize models by fine-tuning hyperparameters, feature selection, or employing regularization techniques to improve accuracy, performance, and scalability- Deep experience in machine learning algorithms, techniques, and best practices
- 3+ year of professional software development experience with a focus in machine learning
- Comprehensive computer science fundamentals in coding, object-oriented programming, data structures, and algorithms
- BS/MS/PhD in Mathematics, Computer Science, Physics, related technical field or equivalent practical experience
- Strong knowledge of machine learning algorithms (e.g., linear regression, SVM, decision trees, neural networks, clustering, etc.) and best practices
- Experience with machine learning algorithms and frameworks, such as TensorFlow, PyTorch, or scikit-learn
- Background with NLP techniques and tools, such as tokenization, stemming, lemmatization, sentiment analysis, and named entity recognition, and libraries like NLTK, SpaCy, or BERT
- Experience with 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)
- 5+ year of professional software development experience with a focus in machine learning
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