Lead applied AI and machine learning research that bridges research and engineering, driving initiatives from problem definition to operational deployment in real-world systems.
Robotic Assistance Devices is seeking an AI Research Staff Engineer to lead applied AI and machine learning research that directly supports product and business outcomes. This role is suited for an experienced practitioner who can lead a team, explore, validate, and deliver AI solutions in a fast-moving, delivery-focused environment. The AI Research Staff Engineer bridges research and engineering—turning ideas, experiments, and models into solutions that can be deployed, measured, and improved in real-world systems.
Key Responsibilities
Lead applied AI and machine learning research aligned with product and business needs.
Design, experiment with, and evaluate models and approaches for real-world use cases.
Drive research initiatives from problem definition through experimentation, validation, and handover to engineering.
Work closely with product, engineering, and operations teams to ensure research outcomes are practical and usable.
Translate research findings into clear recommendations, prototypes, or production-ready solutions.
Balance exploration and delivery by managing research scope, timelines, and trade-offs.
Contribute to improving AI research practices, experimentation workflows, and evaluation methods.
Stay current with relevant advancements in AI and machine learning and assess their practical applicability.
Experience & Qualifications
PhD or Research-based Master’s degree in AI, Machine Learning, Computer Science, Electrical/Electronic Engineering, or a closely related field.
5+ years of experience in AI, machine learning, or related engineering and research roles.
Strong track record of delivering applied AI or ML solutions in business or product-focused environments.
Hands-on experience with model development, experimentation, and evaluation.
Demonstrated ability to align research efforts with product goals and measurable outcomes.
Experience working in startup or fast-paced environments where research must lead to delivery.
Strong problem-solving skills and ability to work with ambiguity.
Clear communication skills, especially in explaining research outcomes to non-research stakeholders.
Nice to Have
Experience in computer vision or vision-based machine learning.
Exposure to deploying or operationalizing ML models.
Experience working with data from real-world systems (noisy, incomplete, evolving).
Familiarity with cloud-based ML workflows and tooling.
What We Offer
Opportunity to work on applied AI research with real-world impact.
Collaboration with experienced engineers, product teams, and leadership.
A role that values practical research, delivery focus, and ownership.
Competitive compensation aligned with local market standards.
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