Requirements
- 4+ years of ML experience at a start-up or larger enterprise high priority
- 6+ months of experience with Large Language Models (LLMs) and Generative AI (GenAI) applications high priority
- Client delivery experience high priority
- Effective written and oral communications skills (C1/C2 advanced/proficient level English is required) high priority
- Bachelors degree in computer science, software engineering or related field
- Experience with cloud environments (e.g., AWS, Azure, GCP)
- Experience with ML frameworks and libraries (TensorFlow, PyTorch, Keras, scikit-learn)
- Experience developing, deploying, and managing/monitoring models
- Knowledge of containerization technologies (e.g., Docker, Kubernetes) and microservices architecture
- Expertise in Object-Oriented Programming (OOP) principles and unit test-driven development methodologies
- Advanced experience in NLP techniques and applications
- Proficiency in Python programming
- Familiarity with prompt engineering approaches and best practices
- Knowledge of data structures, data modeling, and software architecture
- Analytical and problem-solving skills, with the ability to propose innovative solutions and troubleshoot issues
- Ability to work independently and as part of a collaborative team in a fast-paced environment
Experience in any of the following is preferred, not required:
- Agent development
- Data privacy
- Fine tuning LLMs
- LLM architecture and techniques for performance
- MLOps
- ML evaluation
- Model decay and data drift detection and handling
- Pulumi, Terraform and/or Cloud SDKs
- PySpark
- Quantization
- Retrieval-augmented generation (RAG) optimization
- Security
- Vector databases