AI Research Engineer (Temporary Position)

Intel
Mexico, GuadalajaraPosted 27 March 2026

Job Description

Job Details: Job Description: This position requires candidates to upload a resume in English; you are welcome to upload multiple versions of your resume if you prefer but an English version of your resume will be required to be considered for this position. This position is a fixed-term opportunity lasting approximately 12  months The AI Research Engineer will drive advanced algorithmic development and artificial intelligence research to enable next-generation technologies across software, hardware, and intelligent systems. This role focuses on researching, designing, and optimizing AI/ML algorithms and deep learning models that solve complex computational problems, improve system performance, and support innovative product features. You will collaborate closely with cross‑functional engineering teams to translate theoretical models into practical, scalable implementations. Key Responsibilities Research & Innovation Conduct advanced research on emerging technologies, industry trends, and scientific advancements in AI, ML, and deep learning. Identify opportunities for strategic enhancements to existing products or development of new technologies. Define problem boundaries, explore solution spaces, and build proofs of concept or prototypes to validate new ideas. Research, experiment, and innovate to develop new or improved AI/ML algorithms and software products Design and optimize machine learning models and deep learning technologies for enterprise applications Translate theoretical AI models into practical, scalable implementations Collaborate closely with cross-functional engineering teams to integrate AI solutions Product Development & Engineering Support the design, development, and implementation of next-generation AI/ML software products and features. Transform research insights into scalable, production-ready architectures, algorithms, and models. Contribute to midterm and long-term technology roadmaps through data-driven recommendations. Collaboration & Cross-Functional Work Partner with product managers, engineering teams, and technical stakeholders to address critical customer issues with innovative approaches. Collaborate with academic institutions, industry partners, and standards bodies to advance the adoption of emerging technologies. Participate in the creation and refinement of industry standards relevant to AI/ML research and development. Technical Leadership Provide subject-matter expertise in AI/ML methodologies, experimental design, and emerging research directions. Communicate complex technical concepts to both technical and non-technical audiences. Contribute to the development of best practices, frameworks, and reusable components that accelerate innovation. Qualifications: Minimum qualifications are required to be initially considered for this position.  Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates. Minimum Qualifications: Master or Ph.D. program in Computer Science, Computer Engineering, or any related field. 2 years of experience in Computer Graphics, Computer Vision and Robotics. Python and C languages and Linux. Software engineering skills. Git version control, continuous integration and efficient programming. Application of computer vision and robotics state-of-the-art methods on real projects. 3 years working knowledge of ROS. Advance English level. Must have unrestricted, permanent right to work in Mexico (this role is not eligible for visa or immigration sponsorship). Preferred Qualifications: 2 Publication track record in top-tier conference/journal focused on Robotics, Machine Learning, Graphics, etc. Knowledge of 3D sensing and projective geometry. Knowledge and hands on experience with robotics trajectory generation and path planning state of the art algorithms. Minimum Qualifications, you must possess the below minimum qualifications to be initially considered for ... (truncated, view full listing at source)
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