Principal Engineer - AI Platform
W. R. Berkley Corporation1 year ago
Wilmington, DE, USAStaff+
Responsibilities
- Design and develop scalable AI platforms supporting machine learning and deep learning models.
- Collaborate with data scientists to define model infrastructure requirements and optimize platform performance.
- Implement and maintain data pipelines, model deployment strategies, monitoring systems, and high-availability AI services.
- Develop backend systems, REST APIs, and small secure web front ends using Python, R, and/or Java.
- Design database schemas and queries across relational, NoSQL, vector, and graph databases.
- Integrate third-party services including Kafka and Entra ID and coordinate frontend/backend integration.
- Troubleshoot, debug, tune performance, and ensure the scalability, reliability, and security of backend systems.
- Automate repetitive tasks using scripting and configuration management tools.
- Provide technical guidance to teams on AI platform usage and best practices.
- Document platform architecture, workflows, and procedures and stay current with AI and machine learning advancements.
- Lead multiple large-scale data-domain or cross-domain engineering initiatives.
Requirements
- 10+ years of progressive engineering experience developing solutions and leading large-scale data-domain or cross-domain engineering initiatives.
- Proven experience building and maintaining AI or machine learning platforms.
- Strong programming experience with Python, R, and/or Java.
- Experience with AWS or Azure and containerization technologies such as Docker and Kubernetes.
- Experience optimizing code and infrastructure for large datasets.
- Strong knowledge of MySQL, SQL Server, PostgreSQL, MongoDB, CosmosDB, modern vector and graph databases, and Redis or similar caching solutions.
- Experience with Git, GitLab, machine learning frameworks, cloud-based data environments, and production model deployment.
- Knowledge of NLP, AI/ML design and implementation, REST APIs, API gateways, SPAs, data storage, database management, ORM, algorithms, data structures, and software design principles.
- Experience with TensorFlow, PyTorch, or Scikit-learn.
- Experience with structured and unstructured data and technologies such as Redshift, Databricks, Hadoop, Snowflake, Spark, or Kafka.
- Experience with Master Data Management, Data Loss Prevention, encryption or redaction strategies, and protection of sensitive data.
- Understanding of processor architecture and the ability to map use cases to appropriate platforms.
- Bachelor's degree in computer science, information technology, information systems, or a related discipline, with equivalent experience or alternative qualifications considered.
- Preferred qualifications include an advanced degree, big data and MLOps experience, reinforcement learning, generative AI, autonomous systems, insurance AI applications, data science experience, distributed systems, and microservices architecture.
- Strong problem-solving, communication, and collaboration skills.
Benefits
- 10%-20% travel is required.
- The company provides equal employment opportunities.
Tech Stack
Amazon RedshiftApache HadoopApache KafkaApache SparkAWSAzureDatabricksDockerGitJavaKubernetesMicrosoft SQL ServerMongoDBMySQLPostgreSQLPythonPyTorchRRedisscikit-learnSnowflakeTensorFlow
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