Software Engineer – Technical Leadership – Machine Learning
| Company | Meta |
|---|---|
| Location | Boston, MA, USA, Seattle, WA, USA, Burlingame, CA, USA, Menlo Park, CA, USA, New York, NY, USA, Bellevue, WA, USA, Sunnyvale, CA, USA |
| Salary | $213000 – $293000 |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s, PhD |
| Experience Level | Senior, Expert or higher |
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- 12+ years of programming experience in a relevant language OR 8+ years experience with a PhD
- Proven track record of planning multi-year roadmap in which short-term projects ladder to the long-term mission
- Experience driving large cross-functional/industry-wide engineering efforts
- Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions
- Experience communicating and working across functions to drive solutions
- Experience mentoring/influencing executive stakeholders across organizations
Responsibilities
- Drive the team’s goals and technical direction to pursue opportunities that make your larger organization more efficient
- Effectively communicate complex features and systems in detail
- Understand industry & company-wide trends to help assess & develop new technologies
- Partner & collaborate with organization leaders to help improve the level of performance of the team & organization
- Identify new opportunities for the larger organization & influence the appropriate people for staffing/prioritizing these new ideas
- Lead long term technical vision and roadmap for large cross-company efforts
- Suggest, collect and synthesize requirements and create an effective feature roadmap
- Identify and resolve performance and scalability issues, and drive large efforts to reduce technical debt
Preferred Qualifications
- Masters degree or PhD in Computer Science or a related technical field
- Experience with frameworks like TensorFlow, PyTorch, or Scikit-learn
- Knowledge of NLP techniques, including text preprocessing, tokenization, and sentiment analysis
- Understanding of information retrieval concepts, such as indexing, querying, and ranking
- Demonstrated experience with data structures and algorithms, including graph theory and optimization techniques