Machine Learning Information Engineer
Elastic via Stack Overflow
Sep 27th 2018
At Elastic, we have a simple goal: to solve the world's data problems with products that delight and inspire. As the company behind the popular open source projects — Elasticsearch, Kibana, Logstash, and Beats — we help people around the world do great things with their data. From stock quotes to real time Twitter streams, Apache logs to WordPress blogs, our products are extending what's possible with data, delivering on the promise that good things come from connecting the dots. The Elastic family unites employees across 30+ countries into one coherent team, while the broader community spans across over 100 countries.
Machine Learning at Elastic
Machine Learning (ML) for the Elastic Stack allows users to better understand the behavior of their data. We have developed an unsupervised machine learning engine that can plow through large amounts of data and automatically find those insights our users today have been proactively finding using search. Current use cases include finding anomalies within transactions / operational metrics, detecting uncharacteristic user behavior or finding malicious devices.
To help us further expand our capabilities we are looking fo an exceptional individual who can support us in our insatiable appetite for data. This is an amazing opportunity to join a small, highly experienced team where you can make an immediate impact and contribution to the development of our new machine learning offerings.
What you will be doing
To support data driven development of engineering features by becoming a super-user of our ML tool set, by making meaningful data accessible to engineers and in helping to maintain and improve the quality of results. Responsibilities will include:
- Curate and extend data library - develop, acquire and catalog datasets representative of core customer use cases
- Perform data analysis on complex datasets and clearly describe and communicate findings to peers
- Develop ML job configs for known uses cases
- Develop standardized labeling techniques for datasets in our catalog. For example, known outliers or anomalies (unsupervised), or output labels (supervised).
- Build statistical robustness tests for machine learning models against an ever growing data catalog
- Follow GDPR policies, security and data license requirements where applicable
- Highly numerate with education background in Mathematics, Computer Science, Information/Library science, Physics, Engineering or similar
- Solid industry experience working with data; for example as a data analyst, software-, QA engineer or similar
What you will bring
- A proven ability to work with large amounts of data (at least 2 years)
- Able to work as part of a distributed team, having strong collaboration and communication skills
- Detail oriented with a librarian-like approach to organization
- Able to analyse real-world datasets and extract insights according to customer use case
- Knowledge, interest and a real passion for topics in big data, machine learning, data mining and statistical analysis
Experience required in some or all of these areas
- Software engineering (Python, Java, C++)
- Statistical packages and tools (e.g. R, SAS, Octave, MATLAB etc)
- Visualization technologies
- NoSQL or relational databases
We're looking to hire team members invested in realizing the goal of making real-time data exploration easy and available to anyone. As a distributed company, we believe that diversity drives our vibe! Whether you're looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life.
- Competitive pay based on the work you do here and not your previous salary
- Stock options
- Global minimum of 16 weeks of paid in full parental leave (moms & dads)
- Generous vacation time and one week of volunteer time off
- Your age is only a number. It doesn't matter if you're just out of college or your children are; we need you for what you can do.
Elastic is an Equal Employment employer committed to the principles of equal employment opportunity and affirmative action for all applicants and employees. Applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status or any other basis protected by federal, state or local law, ordinance or regulation. Elastic also makes reasonable accommodations for disabled employees consistent with applicable law.