Position Purpose:

The Software Engineer Principal specializing in Machine Learning is responsible for joining a product team and contributing to the software design, algorithm design, and overall product lifecycle for a product that our users love. The engineering process is highly collaborative. In addition to pairing, Software Engineer Principals field questions from other product teams and encourage cross-team collaboration. They also play an active role working with 3rd party vendors as well as the open-source community.

Software Engineer Principals create foundational code elements that can be reused as well as architectural diagrams and other product-related documentation. They also define service level objectives for products. In addition, Software Engineer Principals may be involved in product configuration, performance tuning and testing as well as production monitoring.

As a Software Engineer Principal, you will be an extremely knowledgeable Engineer on the product team and are expected to build and grow the skillsets of the more junior engineers. There is also an expectation that the Software Engineer Principal will demonstrate expertise around modern software design and development.

Key Responsibilities:

70% Delivery & ExecutionCollaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable software solutionsDocuments, reviews and ensures that all quality and change control standards are metWrites custom code or scripts to automate infrastructure, monitoring services, and test casesWrites custom code or scripts to do "destructive testing" to ensure adequate resiliency in productionCreates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactivelyContributes to enterprise-wide tools to drive destructive testing, automation, or engineering empowermentIdentifies product enhancements (client-facing or technical) to create a better experience for the end usersIdentifies unsecured code areas and implements fixes as they are discovered with or without toolingIdentifies, implements, and shares technical solutions that can be used across the organizationCreates and architects foundational code elements that can be reused many times by a productCreates meaningful architecture diagrams and other documentation needed for security reviews or other interested partiesDefines Service Level Objectives for product to constantly measure their reliability in production and help prioritize backlog work20% Support & Enablement:Fields questions from other product teams or support teamsMonitors tools and participates in conversations to encourage collaboration across product teamsProvides application support for software running in productionProactively monitors production Service Level Objectives for productsWorks with vendors and the open-source community to help identify and implement feature enhancements in software productsWorks with other product teams to create API specifications and contracts for shared dataProactively reviews the performance and capacity of all aspects of production: code, infrastructure, data, and message processingTriages high priority issues and outages as they arise10% Learning:Participates in and leads learning activities around modern software design and development core practices (communities of practice)Learns, through reading, tutorials, and videos, new technologies and best practices being used within other technology organizationsAttends conferences and learns how to apply new technologies where appropriate

Direct Manager/Direct Reports:

Typically reports to the Software Engineer Manager or Sr. Manager, Technology Director or Sr. Director.

Travel Requirements:

Typically requires overnight travel less than 10% of the time.

Physical Requirements:

Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

Working Conditions:

Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Minimum Qualifications:

Must be eighteen years of age or older.Must be legally permitted to work in the United States.Mastery of an object oriented programming language (preferably Java)Must be legally permitted to work in the United States

Preferred Qualifications:

6-8 years of relevant work experienceExpertise in ML development and ML ops lifecycleExperience working with multiple leading ML modelsExperience tracking key metrics for ML performanceExperience with architectural patterns to employ AI modelsPerformance tuning applications that leverage ML modelsCapable of understanding complicated systems quicklyExperience in algorithms such as clustering, forecasting, anomaly detection, and neural networks.Experience in basic statistics and regression algorithmsExperience in embeddings generation and utilizationExperience in training machine learning models with extremely large datasetsExperience with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc.Experience with GPU acceleration (i.e. CUDA and cuDNN)Experience in Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML, and AutoMLExperience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etcFamiliarity with Generative AI models and techniques to leverage them in multi-modal contexts

Minimum Education:

The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.

Preferred Education:

No additional education

Minimum Years of Work Experience:

6

Preferred Years of Work Experience:

No additional years of experience

Minimum Leadership Experience:

None

Preferred Leadership Experience:

None

Certifications:

None

Competencies:

Action Oriented: Taking on new opportunities and tough challenges with a sense of urgency, high energy and enthusiasmBusiness Insight: Applying knowledge of business and the marketplace to advance the organization's goalsCollaborates: Building partnerships and working collaboratively with others to meet shared objectivesCommunicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiencesCultivates Innovation: Creating new and better ways for the organization to be successfulDrives Results: Consistently achieving results, even under tough circumstancesGlobal Perspective: Taking a broad view when approaching issues; using a global lensInterpersonal Savvy: Relating openly and comfortably with diverse groups of peopleManages Ambiguity: Operating effectively, even when things are not certain or the way forward is not clearManages Complexity: Making sense of complex, high quantity, and sometimes contradictory information to effectively solve problemsNimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodderOptimizes Work Processes: Knowing the most effective and efficient processes to get things done, with a focus on continuous improvementSelf-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channelsSituational Adaptability: Adapting approach and demeanor in real time to match the shifting demands of different situations