Otto Aviation is seeking to advance its AI initiatives by building production-grade machine learning systems, optimizing model performance, and supporting innovation in next-generation technologies to drive mission-critical decisions across various business functions.
Requirements
- Experience with LLMs, NLP, generative AI, and advanced deep learning techniques.
- Proficiency in scikit-learn, PyTorch, TensorFlow, and distributed training frameworks.
- Knowledge of scalable data pipelines, inference systems, and cloud computing platforms (e.g., AWS, Google Cloud, Azure).
- Familiarity with vector databases, ETL pipelines, and real-time processing systems.
- Hands-on experience with DevOps tools: Docker, Jenkins, Kubernetes, GitHub Actions, Terraform or similar.
- Proficiency in Python and C++ for building production-grade systems.
- Experience with software development practices such as version control (Git), containerization (Docker), and API design.
Responsibilities
- Lead data discovery efforts, framing business problems as data science problems and guiding the team toward data-informed strategies.
- Build, train, validate, and tune machine learning models using advance statistical and machine learning techniques and tools
- Build analytics tools that deliver insights across business functions and domains
- Design, build, and maintain CI/CD pipelines to automate build, test, and deploy workflows.
- Architect solutions using Azure (preferred), AWS, or GCP cloud services for data ingestion, processing, modeling, and serving.
- Champion DevOps culture and promote continuous integration and delivery best practices.
- Stay current with emerging technologies and industry trends in data analytics, machine learning, and IoT.
Other
- A Bachelor's degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) with a minimum of 8 years of experience
- A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) with a minimum of 4 years of experience
- 4 - 8 years of experience in a Full-Stack Data Science, MLOps, or AI Engineering role.
- Strong problem-solving and analytical thinking abilities.
- Excellent communication and collaboration skills to work with cross-functional teams.
