{"id":698145,"url":"https://alion.io/job/qualcomm-genai-engineer-up-to-staff-level","title":"GenAI Engineer (Up to Staff level)","company":{"id":94,"name":"Qualcomm","domain":"qualcomm.com","url":"https://alion.io/company/qualcomm","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"B","score":70,"open_postings":1071,"ghost_share":0.246,"stale_share":0.147,"repost_share":0.457,"time_to_fill_p50_days":74,"computed_at":"2026-10-29T05:49:05Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hanoi, Vietnam","Ho Chi Minh City, Vietnam"],"countries":["VN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":33000,"max_usd":76000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1279},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Diffusion Models","optional":false},{"name":"Edge AI","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Quantization","optional":false},{"name":"Rest-Assured","optional":true}],"status":"live","first_seen_at":"2026-08-24T00:00:00Z","employer_posted_date":"2026-09-08","last_verified_at":"2026-10-29T22:46:47Z","board_verified":true,"closed_at":null,"days_open":66,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":66},"description":"Company:\nQualcomm Vietnam Company Limited, Hanoi Branch OfficeJob Area:\nEngineering Group, Engineering Group > Machine Learning EngineeringGeneral Summary:\nAt Qualcomm AI Research Vietnam, the GenAI Engineer plays a critical role in accelerating adoption of strategic Generative AI models by rapidly evaluating, onboarding, and optimizing LLMs, VLMs, and multimodal models on Qualcomm platforms, including mobile, compute, XR, and other edge AI platforms. This role provides early deployment feasibility and performance insights to support informed product, customer, and business decisions, while delivering production-ready on-device AI experiences that meet latency, memory, power, and accuracy requirements.\nKey Responsibilities\nModel Evaluation & Onboarding: Evaluate strategic GenAI models, including LLMs, VLMs, and multimodal models, and drive onboarding to Qualcomm AI software stacks and target platforms.\n\nQuantization & Optimization Enablement: Enable quantization, model adaptation, and performance optimization workflows to meet platform constraints for latency, memory, power, and accuracy.\n\nOn-device Validation & Benchmarking: Execute on-device validation, downstream benchmarking, and performance analysis to provide early feasibility insights and readiness signals.\n\nCross-stack Debugging: Identify issues early across model, quantization, runtime, backend, and system layers, and drive resolution with system, compiler, runtime, and platform engineeringteams.\n\nRapid Prototype Enablement: Provide early inference support and prototype enablement for new model architectures before the broader ecosystem is fully mature.\n\nProduction-readiness Delivery: Translate research models and early technology IP into robust on-device AI experiences suitable for productization, demos, customer evaluation, and business decision-making.\n\nDocumentation & Knowledge Sharing: Maintain clear technical documentation, benchmark reports, debugging notes, and onboarding guides to improve team execution and cross-team collaboration.\n\nRequirements\nEducation & Background\nBachelor’s or Master’s degree in Computer Science, Electrical Engineering, Artificial Intelligence, Machine Learning, or a related technical field.\n\nHands-on experience with AI/ML model deployment, optimization, benchmarking, or software development for edge, mobile, compute, or embedded platforms.\n\nTechnical & Domain Knowledge\nStrong understanding of GenAI model architectures such as LLMs, vision-language models, diffusion models, or multimodal models.\n\nExperience with model optimization techniques such as quantization, graph conversion, profiling, memory analysis, and runtime performance tuning.\n\nFamiliarity with AI software stacks, inference runtimes, hardware accelerators, and debugging workflows across model, runtime, backend, and system layers.\n\nAbility to analyze benchmark results, identify bottlenecks, and communicate deployment feasibility and performance trade-offs clearly.\n\nSoft Skills\nStrong ownership mindset with the ability to drive technical execution across ambiguous and fast-moving projects.\n\nExcellent problem-solving and debugging skills, with the ability to break down complex cross-stack issues and coordinate resolution with partner teams.\n\nClear communication skills to present technical findings, risks, trade-offs, and recommendations to engineering, product, and leadership stakeholders.\n\nPreferred Qualifications\nExperience with Qualcomm AI software stacks, QNN, NPU acceleration, or similar edge AI deployment toolchains.\n\nExperience onboarding or benchmarking LLMs, VLMs, multimodal models, diffusion models, or other modern GenAI architectures.\n\nExperience collaborating with research, quantization, backend, runtime, system, and product teams to deliver production-ready AI features.\n\nMinimum Qualifications:\n• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.OR\nMaster's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.\nOR\nPhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.\nApplicants: Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail  or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).\nQualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.\nTo all Staffing and Recruiting Agencies:Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. 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