Build the world's best content analytics platform at Parse.ly
Parse.ly is a real-time content measurement layer for the entire web. Our analytics platform helps digital storytellers at some of the web's best sites, such as Arstechnica, The New Yorker, TechCrunch, The Intercept, Mashable, and many more. In total, our analytics system handles over 65 billion monthly events from over 1 billion monthly unique visitors.
We are growing fast and we have five open positions on the product team:
Our data team owns a real-time analytics infrastructure that processes over 2 million pageviews per minute from 2,000 high-traffic sites. It operates a fleet of cloud servers that include thousands of cores of live data processing using cutting-edge technologies like Storm, Spark, Kafka, Cassandra, Elasticsearch, and others. We have written publicly about mage, our time series analytics engine. We have even released popular open source projects in these areas, like streamparse and pykafka. For this role, you should already be a proficient Python programmer who wants to work with data at scale.
Machine Learning Engineer
Parse.ly’s data engineering team already makes use of modern technologies to analyze our large-scale streaming data. We are now expanding into the use of scikit-learn, Spark’s MLLib, TensorFlow, and cloud SQL warehouses like Amazon Athena and Google BigQuery, which will be the purview of our first Machine Learning Engineer. In this role, you will contribute to Parse.ly’s understanding of its own data, and you will deploy your models to enrich and augment this data. For example, key areas of interest include the following NLP tasks over a dataset of 100 million full-text, timestamped articles:
- Detecting temporally and textually coherent ‘stories’, a la Google News
- Extracting entities, assigning them sentiment, and linking them
- Assigning topics/categories from ontologies like Wikipedia
As one of Parse.ly’s first Machine Learning Engineers, you also need to be a strong communicator, so that you can present your findings and your prototypes to the rest of the team. You should feel comfortable rolling up your sleeves to get these models into production and into the hands of customers.
Working in concert with our data engineers and UX engineers, as an infrastructure engineer you will take ownership of Parse.ly’s distributed cloud environment.
This involves 200+ servers running in 7 availability zones and 2 regions in Amazon Web Services. We practice true DevOps: infrastructure-as-code; reliance on automation/scripting; pervasive monitoring/alerting; and, careful distributed system design. In this role, you will code in Python, but be comfortable with scripting languages and orchestration tools. You will master AWS services, security practices, and APIs. You will ensure that one of the most important real-time analytics systems in the world -- trusted daily by over 250 media companies, 2,000 website operators, and over 25,000 active dashboard user seats -- is leveraging the best high-availability and rapid-recovery techniques.
Code + Communication = Success. The goal of a Success Engineer: ensure our customers are delighted with our products, through the wise application of technical know-how, engineering magic, and strong communication skills. You need to love to help people, to write, to solve problems, and to build things. You need to be technical enough to gain deep experience in analytics -- not just our tools, but the tools available in the marketplace, too. You need to stay close to our customers and understand how they use our dashboard, APIs, and infrastructure, as well as how it fits into their broader analytics goals.
As for you, to match well to this role, you’re likely on the junior side of your programming career, so you may not be ready yet for doing day-to-day development on a complex product on your own. But you are willing to learn -- and you're ready to solve specific challenges for customers by building and shipping real code that they will use.
Send a cover letter, CV/resume, and optionally links to projects or code, to the email address here: email@example.com. Make sure to indicate the role you are applying for, choosing from these options:
- UX Engineer
- Data Engineer
- Machine Learning Engineer
- Infrastructure Engineer
- Success Engineer
Note: we have a fully distributed team
Parse.ly is a fully distributed team, with engineers working from across the world.
People with past experience working remotely will be prioritized. Preference will be given for people in ET or CT timezone, but we also accept applications from these time zones, as well: MT, PT, GMT, GMT+1, GMT+2.