About the Role
Key Responsibilities:
- Analyze and identify the linkages and interactions between the component parts of an entire system.
- Take ownership of projects, ensuring their successful planning and technical execution.
- Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables.
- Develop skills outside your comfort zone and encourage others to do the same.
- Use the review of work as an opportunity to deepen the expertise of team members.
- Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate.
Qualifications:
- Bachelor's Degree
- 3 year(s) in a quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, Operational research or equivalent)
- At least 1 year of direct experience with feature identification in developing predictive models, data acquisition and preparation, and hypothesis testing.
- At least 1 year experience in Python, R or other relevant language.
You demonstrate experience in:
- Heavy contributor in building of AI and GenAI solutions, including but not limited to analytical modeling, prompt engineering, general all-purpose programming (e.g., Python), testing, communication of results, front end and back-end integration, and iterative development with clients
- Documenting and analyzing business processes for AI and Generative AI opportunities, including gathering of requirements, creation of initial hypotheses, and development of AI/GenAI solution approach
- Experience processing unstructured and structured data to be consumed as context for LLMs, including but not limited to embedding of large text corpus, generative development of SQL queries, building connectors to structured databases; and
- Demonstrates abilities and/or a proven record of success learning and performing in functional and technical capacities, including the following areas:
- Managing GenAI application including back-end and front-end integrations
- Using Python (e.g., Pandas, NLTK, Scikit-learn, Keras, etc.), common LLM development frameworks (e.g., Langchain, Semantic Kernel), Relational storage (SQL), Non-relational storage (NoSQL);
- Experience in analytical techniques such as Machine Learning, Deep Learning and Optimization
- Vectorization and embedding, prompt engineering, RAG (retrieval augmented generation) workflow development
- Understanding or hands on experience with Azure, AWS, and / or Google Cloud platforms
- Experience with Git Version Control, Unit/Integration/End-to-End Testing, CI/CD, release management, etc.
