Role descriptionJob Title: Applied AI ScientistDesignation: AI Scientist
Location: Canada or United States (US time zones)
Job Summary
We are seeking an exceptional Applied AI Scientist to develop agentic decision systems that empower individuals to make informed decisions. This role focuses on understanding how intelligent systems can effectively reason over complex problems, utilize tools and models, and improve systematically over time. You will tackle ambiguous enterprise challenges, employing a variety of methodologies to enhance decision-making processes.
Responsibilities
- Design and Build: Create agentic decision-support systems that can reason over data, interact with models, and assist in complex human decision-making.
- Systematic Improvement: Develop evaluation frameworks, feedback loops, and benchmarks to identify system failures and validate improvements.
- Quantitative Problem-Solving: Define measurable objectives, analyze performance distributions, and differentiate genuine improvements from mere metric shifts.
- Architectures Exploration: Investigate self-improving agentic architectures, including adaptive tool selection and policy improvement mechanisms.
- Statistical and ML Application: Apply Statistical Modelling and AI / ML (Artificial Intelligence & Machine Learning) Algorithms techniques to enhance system reliability and usability.
- Software Development: Utilize AI coding systems to generate high-quality software, focusing on excellence rather than volume of code.
- End-to-End Ownership: Manage complex problems from initial formulation through design, implementation, evaluation, and deployment.
- Challenge Assumptions: Question problem definitions and optimize solutions based on rigorous analysis.
- Stakeholder Engagement: Communicate complex ideas clearly to technical and business stakeholders, making assumptions and limitations explicit.
Mandatory Skills
- Strong quantitative foundation in mathematics, physics, statistics, engineering, or related fields.
- Hands-on experience in designing or developing agentic systems, including multi-step reasoning and planning.
- Proficiency in Statistical Modelling and AI / ML (Artificial Intelligence & Machine Learning) Algorithms, with a solid understanding of uncertainty, validation, and experiment design.
- Ability to produce high-quality software using AI coding systems, with a focus on architecture and code quality.
- Strong analytical thinking and problem-solving skills, with a willingness to question assumptions and redefine problems.
Preferred Skills
- Experience in decision science, causal inference, or Optimization techniques.
- Familiarity with reinforcement learning, simulation, or adaptive experimentation.
- Knowledge of agent evaluation and performance improvement mechanisms.
- Experience in complex enterprise decision environments such as finance, insurance, or logistics.
Qualifications
A master's or PhD in a quantitative discipline is preferred, but exceptional candidates with a bachelor's degree and strong analytical skills will also be considered. Candidates should be comfortable reasoning mathematically about unfamiliar problems and possess a deep curiosity for understanding complex systems.
Join us at Mphasis, where we leverage next-generation technology to transform enterprises globally. We are committed to fostering an inclusive environment and welcome applications from all qualified candidates.
