Staff Software Engineer, Machine Learning

Our Mission:

To actively connect people to their next great opportunity.

Who We Are:

ZipRecruiter is a leading online employment marketplace. Powered by AI-driven smart matching technology, the company actively connects millions of all-sized businesses and job seekers through innovative mobile, web, and email services, as well as through partnerships with the best job boards on the web. ZipRecruiter has the #1 rated job search app on iOS & Android.

Summary:

With data such as a billion+ historical job postings, tens of millions of active job seekers interacting with our system, and hundreds of billions of impression and click events, there are incredible opportunities to use your skills to build new data-driven features. Working at ZipRecruiter, you will be helping literally millions of people find their dream job. We’re working on problems like: given a training set of job postings, and known salaries, build a system that predicts salary for novel jobs.Of course, you know that while building models is fun, it's also just one step in the process; gathering training data, cleansing it, digging into it, extracting features from it, etc, is a huge part of the job

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

The US base salary range for this full-time position is $180,000-$225,000. Our salary ranges are determined by role, level, and location, and the range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location, role-related knowledge and skills, depth of experience, relevant education or training, and additional role-related considerations.

Depending on the position offered, equity, bonuses, commission, or other forms of compensation may also be provided as part of a total compensation package, in addition to a full range of medical, financial, and other benefits.

Originally posted on Himalayas