- Develop LLM-powered solutions such as RAG architectures on proprietary knowledge repos, querying unstructured data with natural language, and content generation
- Build, scale, and optimize data science workloads and apply best in class MLOps to productionize these workloads across a variety of domains
- Build ML Pipelines to train, serve and monitor reinforcement learning systems in production using Databricks
- Collaborate with data engineering and data science teams to innovate and establish best practices for MDLC and LLM evaluation frameworks
- Collaborate with the product and client services teams to define priorities and influence product roadmap
- Mentor junior AI/ML engineers, guiding them in building a modern AI infrastructure and developing responsible AI solutions
- 6+ years of related experience with a Bachelor's degree; or 3+ years and a Master's degree; or a PhD with 1 year experience
- Experience with the latest techniques in natural language processing including vector databases, fine-tuning LLMs, RAG, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI
- 5+ years of hands-on industry data science or machine learning experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, gensim, nltk, and TensorFlow/PyTorch
- Highly proficient on Databricks ML and MLFlow
- Experience building production-grade machine learning deployments on Databricks
- Proven leadership skills, a strategic mindset, and a passion for driving innovation in AI/ML technology
- Exceptional stakeholder management and communication skills to effectively communicate across global teams
- Experience with Knowledge Graphs and Graph Databases like Neo4j
- Experience with Delta Lake and Unity Catalog
- Experience working with Apache Spark to process large, distributed datasets
- Experience developing customer behavioral scoring or propensity models
- Experience or knowledge of working in a compliance-based environment, including building and deploying compliant software solutions throughout the software life cycle
- Paid Time Off
- Comprehensive benefits plan
- Company RRSP Match
- Development opportunities through the LinkedIn Learning platform
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Senior ML Engineer - Toronto, Canada - Guidepoint
Description
:Guidepoint seeks an experienced ML Engineer as an integral member of the Toronto-based Data/AI team. The Toronto Technology Hub will serve as the base of our new Data/AI team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint's vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint's Next-Gen research enablement platform and data products.
This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and advanced data products leveraging latest trends in LLMs, MLOps and ML more broadly. The Senior/Lead ML Engineer is a member of an ensemble team of inter-disciplinary specialists and will be a primary contributor to developing AI/ML capabilities using Databricks across all of Guidepoint's products.
More about Guidepoint's Technology Team:
Guidepoint's Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services.
This position can be hybrid in the Toronto area.
Your Day-to-Day Will Include:
Minimum Qualifications:
Preferred Qualifications:
What we Offer
About Guidepoint
Guidepoint is a leading research enablement platform designed to advance understanding and empower our clients' decision-making process. Powered by innovative technology, real-time data, and hard-to-source expertise, we help our clients to turn answers into action.
Backed by a network of nearly 1.5 million experts, and Guidepoint's 1,300 employees worldwide we inform leading organizations' research by delivering on-demand intelligence and research on request. With Guidepoint, companies and investors can better navigate the abundance of information available today, making it both more useful and more powerful.
At Guidepoint, our success relies on the diversity of our employees, advisors, and client base, which allows us to create connections that offer a wealth of perspectives. We are committed to upholding policies that contribute to an equitable and welcoming environment for our community, regardless of background, identity, or experience.
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