AI Engineer/ Sr AI Engineer
- Toronto, ON
- Permanent
- Full-time
As a Senior AI Engineer, you'll be working with a global team of AI and machine learning practitioners, software engineers, and business and solution architects to implement state of the art - AI enabled digital solutions to transform the P&C insurance globally. This position offers the opportunity to develop, deploy, and optimize Large Language Models (LLMs) that deliver high quality AI products.Major Responsibilities:
- Work closely with team of AI engineers to design, build, and serve LLMs to solve complex business challenges using Azure (CPU & GPU environments)
- Researching & implementing state of the art LLM techniques including pre-training, fine-tuning, preference alignment, and deployment while also focusing on prompt engineering and generative AI more broadly
- Heavily focusing on developing novel data sets that enable LLMs to perform new tasks as well as tooling/platforming to collect these samples at scale. You will need strong python data fundamentals coupled with a software mindset for making data processing and collection pipelines repeatable, scalable, and high quality.
- Ensure high quality code that meets business objectives, quality standards and development guidelines.
- Building reusable pipelines, processes, and tools to streamline LLM and generative AI workflows
- Manage project stakeholder expectations and issue communications on progress.
- React to shifting priorities without compromising deadlines and momentum.
- Must have:
- 5 + years' experience in AI Engineering and/or Machine Learning (ML) with a focus on LLMs, with deep expertise in writing, and reviewing production code in Python.
- Understanding the development lifecycle for LLMs- developing data sets for pre-training, instruction tuning, and preference alignment alongside the modelling techniques for each stage and LLM deployment is as MAJOR plus.
- Multi-disciplinary approach to problem solving, including excellent interpersonal and communication skills (written and verbal). This includes crisply talking about technical solutions while being able to collaborate with business architects effectively.
- Strong knowledge of LLM frameworks and libraries (such as transformers, trl, deepspeed, PyTorch), and exposure to various ML techniques and their practical implementation in production at large scale.
- Experience on distributed, high throughput and low latency architectures
- Strong fundamentals in NLP techniques for text representation, semantic extraction techniques, data structures and modeling.
- Experience building software on top of major container technology (Kubernetes, Docker etc.)
- Nice to have:
- Experience defining system architectures and exploring technical feasibility tradeoffs is a huge plus
- Familiarity with end-to-end application development using full stack is a plus.
- Experience in P&C insurance is a plus.