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Senior Software Development Engineer for AI Data Management
hace 2 meses
We are seeking an experienced Senior Software Development Engineer to lead the design and implementation of innovative, scalable data solutions for our AI Data Management team. As a key member of our team, you will work across multiple SDE organizations, Applied Science teams, and partner groups to build flexible, resilient data pipelines that enable our researchers to access high-quality training data just-in-time.
Key Responsibilities- Conduct a comprehensive analysis of existing annotation workflows and develop/implement automation tools to streamline manual tasks.
- Design and deploy scalable, fault-tolerant data collection, annotation, and delivery pipelines to support the growing needs of our Applied Science teams.
- Collaborate with SDE, Data Engineering, and Applied Science teams to define requirements and ensure seamless integration of data solutions.
- Automate data workflows and build reusable, self-service capabilities to increase the speed and agility of our data delivery.
- Proactively identify and mitigate technical risks, demonstrating solid judgment in determining when to escalate.
- Foster a culture of testing, monitoring, and continuous improvement across data systems.
- Experience as a full-stack software engineer, with a track record of delivering highly scalable, mission-critical data systems.
- Proficiency in designing and building distributed, fault-tolerant data pipelines and batch/streaming data processing workflows.
- Strong programming skills in languages like Java, Python, Scala, or Golang, with a deep understanding of software engineering best practices.
- Hands-on experience with modern data storage and processing technologies, such as Kafka, Spark, Hadoop, Cassandra, Redshift, or BigQuery.
- Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and infrastructure-as-code tools (e.g., Terraform, CloudFormation).
- Expertise in developing and implementing robust monitoring, alerting, and automated remediation for data systems.
- Experience with agile software development methodologies and tools (e.g., Jira, GitHub, CI/CD pipelines).
- Strong analytical and problem-solving skills, with the ability to tackle ambiguous, complex challenges.
- Excellent verbal and written communication skills to effectively collaborate with cross-functional teams.
- Experience designing and building large-scale data platforms to support machine learning and artificial intelligence use cases.
- Track record of delivering complex, cross-functional data projects that drive measurable business impact.
- Familiarity with data engineering best practices around data quality, lineage, governance, and lifecycle management.
- Understanding of machine learning data workflows, including data collection, annotation, feature engineering, and model training/deployment.
- Knowledge of data privacy and security frameworks (e.g., GDPR, CCPA) and experience implementing solutions to address compliance requirements.
- Familiarity with low-code/no-code development tools and their application in data automation and self-service capabilities.
- Proven ability to mentor and lead more junior engineers, fostering their technical growth and career development.
- Experience in delivering presentations and technical roadmaps to executive-level stakeholders.
