The world is changing at an accelerating rate. But we cannot take in the information fast enough, let alone make sense of it. We are fundamentally limited by the speed at which we read and write — the speed of human thought. The challenges facing decision-makers today require a radically new technology.
Primer is at the forefront of the natural language processing revolution. Our artificial intelligence platform is capable of reading text at a rate of millions of documents per hour, extracting information and updating a knowledge graph of billions of entities. It is capable of answering natural language questions and generating the first draft of natural language analytical reports in seconds. Our mission is to empower our customers by vastly reducing the cost of curiosity. What once took days of research can happen instantly.
Our customers include some of the world’s largest corporations, financial institutions, and government agencies in the world. You can learn more about Primer’s technology and the problems we solve at our blog, as well as in recent media coverage of our work.
At Primer, we put our customers first. As a Senior Technical Delivery Manager, you’ll guide client engagements from ideation to deployment for some of the world’s largest enterprises. You’ll be responsible for understanding client needs through data, conversations, and any other means necessary. You’ll work closely with Engineering, Design, and Sales. You’ll face problems that require a mix of technical knowledge, creativity, critical thinking, and business acumen.
Primer is an Artificial Intelligence company that organizes and analyzes text-based data sources and generates analyst-grade natural language summaries for a variety of industries. Our objective is to help our customers understand the world around them ‐‐ whether it is emerging geopolitical events, development of a product line or area of research, or monitoring a portfolio of companies’ financial performances.
The Services team is a jack-of-all-trades organization that serves as a key interface between individual clients and the broader Primer organization. Our charter is: (1) work closely with clients to discover the best use of Primer’s NLP/NLG algorithms for their needs; (2) prototype new algorithms, data pipelines, and visualizations; and (3) channel client feedback and algorithmic learnings back to Primer to drive future product development.
- Roadmap: Work with clients, the business, and engineers to set strategy and collect and prioritize requirements.
- Execute: Work with data scientists, machine learning engineers, software engineers, and designers to build products that delight our customers.
- Generalize: Think widely about potential applications of machine learning and natural language processing techniques, translating capabilities built for individual clients into new features or customization options for our core products.
- United States citizenship is required for this position as a result of contractual requirements with the United States government
- Background data science, NLP, software engineering, and/or UI design
- Minimum 5 years of relevant experience
- 2+ years either working as a data scientist/ML engineer, or collaborating with data scientists/ML engineers
- 3+ years of product/project management, product design, or equivalent consultant experience for a technology company
- Coding experience, either professional or in a self-taught enthusiast capacity
- Academic background in Computer Science, Engineering, or quantitative discipline
- Strong analytical capability with experience in data modeling and analysis
- Demonstrated success in delivering new products and features
- Ability to make things happen around you, and a desire to contribute and learn. You manage project ambiguity, complexity, and cross-functional interdependencies in an organized and structured way. Be able to define and analyze metrics that inform the success of products
- You are located in San Francisco, Washington D.C., or Denver
- Familiarity with machine learning modeling workflows and basics of Data Science (e.g., classification vs. regression, feature selection and engineering, different machine learning model families, optimization considerations for machine learning models, deployment and serving challenges)
- Familiarity with machine learning algorithms, databases, constructing data pipelines
- Experience prototyping on software products with customers