Software Engineer II - AI/ML
Description
Job Requirements:
- 5 - 7 years of hands-on experience in AI/ML engineering, including Machine Learning, Deep Learning, statistical modeling, and data modeling on large-scale datasets.
- Strong experience in Generative AI, Large Language Models (LLMs), and Agentic AI, including building AI agents and production-grade AI applications.
- Proficiency in ML model development using Python, TensorFlow, PyTorch, and related ML libraries.
- Experience with Agentic AI platforms such as Glean and Agent Bricks, and orchestration frameworks such as LangChain.
- Experience with LLM evaluation, observability, and monitoring tools such as Langfuse and LangSmith.
- Strong programming and API development skills using Python, FastAPI, and SQL.
- Experience working with databases and large-scale data technologies such as MySQL, PostgreSQL, MongoDB, and Spark SQL.
- Strong understanding of data structures, design patterns, automation, and software engineering best practices.
- Experience with real-time/streaming technologies such as Kafka and Amazon Kinesis.
- Hands-on experience in developing, deploying, and productionizing AI/ML applications using Docker and Kubernetes.
- Familiarity with Git-based version control, preferably Azure Git/Azure DevOps.
- Proven experience in leading AI/ML projects end-to-end, from business requirements and solution design through development, deployment, and production support.
- Ability to translate business requirements into scalable technical and AI/ML solutions.
- Experience leading and mentoring team members, along with strong written and verbal communication skills.
- Bachelors degree in Computer Science, Engineering, Data Science, or an equivalent discipline.
- Retail industry experience is a strong plus.
Skills
- Agentic AI
- AI
- API
- Automation
- Azure
- Azure DevOps
- Data Modeling
- Data Science
- Deep Learning
- Design Patterns
- DevOps
- Docker
- FastAPI
- Generative AI
- Git
- Kafka
- Kinesis
- Kubernetes
- LangChain
- Langfuse
- LangSmith
- LLM
- Machine Learning
- MongoDB
- MySQL
- Observability
- PostgreSQL
- Python
- PyTorch
- Solution Design
- Spark
- SQL
- TensorFlow
- Version Control


