AI Engineer II-1

Skills

Computer ScienceFront-End DevelopmentWarehouse OperationsDatabasesDriftReadinessTechnical Solution Design

Role

What the job involves

The main requirements, responsibilities and hiring steps.

Bachelor’s degree in Computer Science Data Science Engineering or related field
Master’s degree preferred
2+ years hands-on experience with a deep learning framework
Experience independently building training and iterating multiple ML models
Strong coding skills in Python Java or C++
Experience with API development and software design
Deep understanding of machine learning concepts including classification regression clustering and deep learning
Hands-on experience with PyTorch TensorFlow or similar frameworks
Experience with LLMs prompt engineering fine-tuning LangChain or LangGraph
Experience with RAG systems
Experience with data wrangling SQL data warehousing and ETL pipelines
Experience with SQL and NoSQL databases
Solid software engineering practices including Git automated testing and CI/CD
Experience with Docker and Kubernetes
Experience with model monitoring drift lineage telemetry and traceability
Experience with canary shadow and comprehensive testing strategies
Experience building and consuming RESTful APIs
Proficiency with at least one cloud platform such as GCP AWS or Azure
Experience with AI or ML cloud services such as Vertex AI SageMaker or Azure ML
Experience with Apache Spark or similar big data technologies
Experience with React Vue.js Angular or similar frontend frameworks

Design and build production-ready AI and machine learning solutions that power automation predictive insights and advanced analytics
Develop scalable ML pipelines AI agents and data workflows then deploy monitor and maintain them in enterprise systems
Collaborate with data scientists engineers and platform teams to move prototypes into governed business-ready services
Implement observability SLOs alerting incident response and rollback plans to ensure reliable AI operations