Machine Learning Engineer
- Austin, TX
At Cloudflare, we have our eyes set on an ambitious goal: to help build a better Internet. Today the company runs one of the world’s largest networks that powers trillions of requests per month. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare have all web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was recognized by the World Economic Forum as a Technology Pioneer and named to Entrepreneur Magazine’s Top Company Cultures list.
We realize people do not fit into neat boxes. We are looking for curious and empathetic individuals who are committed to developing themselves and learning new skills, and we are ready to help you do that. We cannot complete our mission without building a diverse and inclusive team. We hire the best people based on an evaluation of their potential and support them throughout their time at Cloudflare. Come join us!
About the department
Cloudflare is looking to grow our Business Intelligence team responsible for enabling various product and business teams such as Marketing, Sales, Finance,Customer Support, Infrastructure teams with data and analytics. Our team currently has Data Engineers, Data Analysts, and Data Scientists and we are looking to add a Machine Learning Engineer to help scale our ML platform and models.
What you'll do
- Partner and align with data scientists, business leaders, stakeholders, product managers and internal teams to enable machine learning solutions to key business problems..
- Understand data landscape i.e tooling, tech stack, source systems etc. and work closely with the data engineering team to improve the data collection and quality.
- Work with data scientists to ensure best engineering practices in the deployment, maintenance, and delivery of machine learning models and insights.
- Use software engineering best practices to publish model scores/insights/learnings at scale within the company.
- Strong communication skills to communicate between engineering, data science, and product management teams. Use storytelling skills to communicate in a crisp and concise manner.
- Build machine learning pipelines, feedback loops, experimentation environments, and rich data sets.
- Understand business/product strategy and high-level roadmap and align model development efforts to help achieve strategic goals.
- Active role in hiring, growing, and mentoring the data scientist team in Austin.
Examples of desirable skills, knowledge and experience
- M.S or Ph.D in Computer Science, Statistics, Mathematics, or other quantitative fields.
- Strong experience in scientific computing using Python, R, or Scala.
- Experience with Spark, SQL, Tableau, Google Analytics, Hive and BigQuery (or any other Big data/Cloud equivalent) etc.
- Experience working with and processing structured, unstructured, and semi-structured data.
- Work closely with the data engineering team to ensure robust data pipelines and model deployment.
- 5+ years of engineering experience with proven industry experience in a large scale machine learning deployment environment.
- 2+ years experience with a fast-growing SaaS business based company is preferred.
- Strong communication and presentation skills catered to different audiences within the company.
- Capable of working closely with business, engineering, and product teams to ensure machine learning initiatives are aligned with business needs.
- Experience in fast prototyping and establishing team engineering best practices is preferred.
- Experience with container based deployments such as Docker & Kubernetes.
- Experience in building RESTful and microservices applications.
What Makes Cloudflare Special?
We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet.
Project Galileo: We equip politically and artistically important organizations and journalists with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost.
Athenian Project: We created Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration.
Path Forward Partnership: Since 2016, we have partnered with Path Forward, a nonprofit organization, to create 16-week positions for mid-career professionals who want to get back to the workplace after taking time off to care for a child, parent, or loved one.
Sound like something you’d like to be a part of? We’d love to hear from you!
Cloudflare is proud to be an equal opportunity employer. We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness. All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer.
Cloudflare provides reasonable accommodations to qualified individuals with disabilities. Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. If you require a reasonable accommodation to apply for a job, please contact us via e-mail at email@example.com or via mail at 101 Townsend St. San Francisco, CA 94107.
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