AI Research Staff Engineer

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.