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Software Engineer - Machine Learning Platform



Software Engineering
United States
Posted on Thursday, July 7, 2022

At Lacework, we strive to provide a supportive, collaborative environment where people are empowered to do the best work of their careers.

Our team members enjoy solving complex problems, big sky thinking, and obsess over getting the details right. We love what we do and are proud of our work to secure clouds and container environments for thousands of users worldwide.

The Role: We are looking for a software engineer in the Machine Learning Platform team to join one of Lacework’s essential groups developing and optimizing machine learning platform services. The ideal candidate is a ML or software engineer who is passionate about machine learning, cloud security, and directly addressing customer-facing issues. This team focuses on delivering ML products while solving engineering challenges at scale. Given the fast-moving nature of this space, candidates should have a learner’s mindset. The responsibilities for this role include:

  • Develop an in-depth understanding of the Lacework platform and customer value proposition
  • Understand the competitive product landscape and Lacework differentiation
  • Drive projects/technical initiatives related to ML platform engineering
  • Influence and define delivery timelines in alignment with our field and product teams while balancing speed, accuracy and precision
  • Build instrumentation, observability, and analytics into the machine learning services to support data-driven decisioning and incident response
  • Work with leadership to track key performance, cost, and efficiency metrics as service level objectives (SLOs)
  • Partner with our security efficacy team to mutually enhance our detection quality
  • Build strong cross functional partnerships (ML research, data platform, cloud economics, etc)
  • Demonstrate good communication skills and present work to company leadership and at company-wide events
  • Actively participate in recruiting and mentor new members of the team
  • Strive to use readily available, general and scalable methodologies and tools; stay current with latest tools and techniques

Minimum Qualifications

  • Degree in quantitative field (e.g. Computer Science, Engineering, Mathematics, Statistics, Operations Research or other related field)
  • 4+ years of experience with software development and deployment using modern cloud platforms
  • Strong experience developing data-intensive applications
  • Experience with developing machine learning applications
  • Hands-on design and development of Go and/or Java-based microservices
  • Exposure to modern software delivery release models and associated tooling (CI/CD, monitoring, observability)
  • Ability to deal with ambiguity, driving design and implementation to conclusion with limited supervision

Preferred Qualifications

  • Advanced degree (Master’s or PhD or equivalent experience) in a quantitative field
  • Experience of ML Ops and CI/CD integrations and tools
  • Experience with data processing/ML platform tools (sagemaker, tensorflow, spark, etc.)
  • Familiarity with cloud-based data warehouses (snowflake, redshift, etc.)
  • Familiarity with data streaming solutions (kafka, spark streaming, etc.
  • Experience working in Cloud Security or Infrastructure Security
  • Experience recruiting and mentoring other Engineers
  • Cloud certifications or other demonstrable cloud domain knowledge

Salary Range: $137k - $300k USD Annually + Benefits + Bonus + Equity

Actual compensation may vary based on factors such as geographic location, work experience, education/training and skill level.

Location: Mountain View, CA | Seattle, WA | Ireland | United Kingdom

Lacework is an Equal Opportunity Employer. It is the policy of Lacework to provide equal employment opportunity to all persons, regardless of age, race, religion, color, national origin, sex, political affiliations, marital status, non-disqualifying physical or mental disability, age, sexual orientation, membership, or non-membership in an employee organization, or on the basis of personal favoritism or other non-merit factors, except where otherwise provided by law