À propos de ce poste Applied Research Scientist chez Evolver
Evolver · Toronto, Ontario or Palo Alto, California
We are an innovative AI startup focused on transforming professional services through cutting-edge Generative AI and deep domain expertise. Our agent-driven solutions automate complex workflows, engaging humans only when needed to maximize efficiency and accuracy. Join us at the forefront of AI innovation, where your expertise will directly shape the future of professional services.
About the Role
We are looking for an experienced researcher with a passion for Generative AI and hands-on expertise in cloud development. As an Applied Research Scientist, you will lead the design, development, and deployment of scalable GenAI applications that redefine how professional services are delivered. You will work in small teams to own delivery of high-stakes projects with clients, much like a hands-on AI startup CTO. A day’s work may include building LLM workflows on a large scale, interacting with customers to understand their needs and set their AI strategy, but the most impact will be driven by implementing solutions into the real world of our partner's organizations. Your work will contribute to extending our existing footprint and strategy into new markets and problem spaces opened by Gen AI.
Proven track record of achieving significant results demonstrated in grants, fellowships, patents and publications in top-tier AI conferences (AAAI, ICLR, Neurips); NLP venues (ACL, EMNLP); or computer vision venues (CVPR, ICCV).
Responsibilities
• Innovation: Stay ahead of emerging trends in AI and GenAI to continuously elevate our technical capabilities.
• Publish: We encourage collaborations with universities, and inter-disciplinary research to ensure our work is open-access, and for our research to remain at the forefront of innovation.
• Mentorship: Guide and support junior researchers and engineers to foster technical growth within the team.
• GenAI Development: Support engineering teams for building a platform for enterprise GenAI solutions leveraging large language models (LLMs) and state-of-the-art frameworks.
• Cloud Development: Design and implement robust, cloud-native solutions, preferably on Azure.
• Model Optimization: Fine-tune LLMs, enhance data retrieval from structured/unstructured sources, and optimize prompt engineering and agent plans.
• Collaboration: Work closely with cross-functional teams, including domain experts and product managers, to deliver solutions aligned with business needs.
Qualifications
Education:
• Ph.D. in Computer Science, Engineering, Neuroscience, Robotics, or a related field.
Experience:
• 5+ years of professional experience in Python development, including deploying machine learning or Generative AI applications.
• 5+ years research experience related to next-generation technologies (multi-modal systems, neuro-symbolic AI, agents, reinforcement learning, domain adaptation, and alignment).
• 2+ years of hands-on experience building and deploying AI/ML solutions in Azure.
Technical Skills:
• Advanced proficiency in Python and libraries such as PyTorch, Tensorflow, JAX or similar.
• Experience with Cloud development, preferably Azure (e.g., Azure App Service, Azure Functions, Azure Database Services, Azure AI services, and Azure Search).
• Experience with LLMs from OpenAI, Anthropic, Google, or Meta and their application in chatbots, RAG systems, and agents.
• Familiarity with GenAI frameworks like LangChain, DSPy, or equivalent tools.
Soft Skills:
• Excellent communication and collaboration skills in team-driven environments.
• Analytical mindset with a strong focus on problem-solving.
• Comfortable working in a fast-paced, dynamic startup culture.
• Eagerness to learn and contribute to cutting-edge technologies.
Benefits
• Competitive Compensation: Tailored to your experience and skill set.
• Flexible Work Arrangements: Hybrid working model for work-life balance.
• Career Growth: Opportunities for professional development and leadership roles.
• Innovative Culture: Work on transformative technologies and make an impact in the AI space.
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