Staff Machine Learning Engineer

As a Staff Machine Learning Engineer you will take the lead on building new or updating data driven product features. This will be achieved by leveraging, implementing, and scaling cutting edge algorithms and performing solid software engineering to make sure that what you build is performant and scales. You will have a strong product sense and intuition about data so that you can build impactful features for our customers. You will partner with cross functional teams composed of product managers, frontend/backend engineers, and other technical leaders to solve the technical challenges of our machine learning technology. You’ll be constantly learning and constantly teaching, expanding your skills across the stack and bringing in new technologies and methods to the team.

Roles and Responsibilities - How You Will Make an Impact

• Understand the landscape of NLP problems and identify strategic investments which ensure Primer’s ability to lead in the space
• Develop architecture, libraries and systems with company wide impact. Help teams on architectural practices to create integrated Primer products
• Collaborate and influence cross-functional teams to drive technical roadmap and build foundational blocks that help deliver on the broader company goals
• Lead and mentor engineers to help them grow
• Scale and optimize NLP models and pipelines for our products
• Improve and promote engineering best practices across the company and motivate other engineers to follow high standards

Relevant Skills and Experience

• MSc. or PhD. in computer science, statistics, computational linguistics, or related fields
• Strong programming skills, including in Python, with at least 5 years experience in a production engineering team
• At least 5 years building analytical/data driven products in an industry setting developing and deploying machine learning and NLP-based solutions
• Hands-on experience with machine learning and NLP tools and libraries including Numpy, Scipy, Scikit-learn, SpaCy, NLTK, Torch, Tensorflow, Keras
• Deliver ML systems that can scale to millions of documents
• Collaborate with the research team to train and ship state of the art models
• Experience taking ambiguous problem statements through to delivered products
• Experience working with cloud (AWS or Azure) and container technologies
• Curiosity, enthusiasm, and a love for teaching and learning

This role will consider applicants out of San Francisco, CA or Washington, DC

The annual cash compensation range for this position is US$225,000 to US$250,000. Final compensation will be determined based on experience and skills and may vary from the range listed above.