Software Engineer (Technical Leadership) - Machine Learning 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

Minimum Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
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
12+ years of programming experience in a relevant language OR 8+ years experience with a PhD

Preferred Qualifications

Demonstrated experience with data structures and algorithms, including graph theory and optimization techniques
Experience with frameworks like TensorFlow, PyTorch, or Scikit-learn
Understanding of information retrieval concepts, such as indexing, querying, and ranking
Masters degree or PhD in Computer Science or a related technical field
Knowledge of NLP techniques, including text preprocessing, tokenization, and sentiment analysis
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

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