{"id":1105682,"url":"https://alion.io/job/qualcomm-machine-learning-engineer-generative-ai-2","title":"#Machine Learning Engineer - Generative AI","company":{"id":94,"name":"Qualcomm","domain":"qualcomm.com","url":"https://alion.io/company/qualcomm","size_band":"5000+","is_staffing_agency":false,"is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"B","score":79,"open_postings":1326,"ghost_share":0.13,"stale_share":0.092,"repost_share":0.403,"time_to_fill_p50_days":76,"computed_at":"2026-09-24T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Diego, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":114500,"max":171700,"currency":"USD","period":"year","gross":null,"usd_annual":171700},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"Fine-tuning","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"RAG","optional":false},{"name":"Agile","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Chain-of-Thought","optional":true},{"name":"GCP","optional":true},{"name":"LangChain","optional":true},{"name":"LlamaIndex","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"Reinforcement Learning","optional":true},{"name":"Rest-Assured","optional":true},{"name":"TensorFlow","optional":true},{"name":"Transformers","optional":true}],"status":"live","first_seen_at":"2026-09-18T00:00:00Z","employer_posted_date":"2026-09-18","last_verified_at":"2026-09-24T02:55:38Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":6},"description":"Company:\nQualcomm Technologies, Inc.Job Area:\nEngineering Group, Engineering Group > Modem Technologies SoftwareGeneral Summary:\n*** This position is not eligible for Qualcomm immigration sponsorship.***\nWe are seeking an experienced Machine Learning Engineer specializing in Generative AI to join our core AI team.\nThe ideal candidate will be responsible for designing, developing, and deploying cutting-edge generative AI solutions, with a focus on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Intelligent agent systems.\nKey Responsibilities:\nDesign and implement RAG-based solutions to enhance LLM capabilities with external knowledge sources\n\nDevelop and optimize LLM fine-tuning strategies for specific use cases and domain adaptation\n\nCreate robust evaluation frameworks for measuring and improving model performance\n\nBuild and maintain agentic workflows for autonomous AI systems\n\nCollaborate with cross-functional teams to identify opportunities and implement AI solutions\n\n Minimum Qualifications:\n• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field.Preferred Qualifications:\nExperience with popular LLM frameworks (Langchain, LlamaIndex, Transformers)\n\nKnowledge of prompt engineering and chain-of-thought techniques\n\nExperience with containerization and microservices architecture\n\nBackground in Reinforcement Learning\n\nContributions to open-source AI projects\n\nExperience with ML ops and model deployment pipelines\n\nSkills and Competencies:\nStrong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow)\n\nPractical experience with LLM deployments and fine-tuning\n\nExperience with vector databases and embedding models\n\nFamiliarity with modern AI/ML infrastructure and cloud platforms (AWS, GCP, Azure)\n\nStrong understanding of RAG architectures and implementation\n\nStrong problem-solving and analytical skills\nExcellent communication and collaboration abilities\n\nExperience with agile development methodologies\n\nAbility to balance multiple projects and priorities\n\nStrong focus on code quality and best practices\n\nUnderstanding of AI ethics and responsible AI development\n\nQualcomm 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).\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. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.\nEEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.\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.\nPay rangeand Other Compensation & Benefits :\n$114,500.00 - $171,700.00The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer - and you can review more details about our US benefits at this link.\nIf you would like more information about this role, please contact Qualcomm Careers.","description_format":"text","description_chars":5011,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Semiconductors","Wireless","Car Electronics"],"lifecycle":[{"event":"open","at":"2026-09-22T04:38:12Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":6,"expected_fill_days":76,"reasons":["conf:2","velocity","win:early","comp:brand"],"computed_at":"2026-09-24T05:45:00Z"},"pay":{"stated_usd_annual":171700,"is_top_pay":false},"html_url":"https://alion.io/job/qualcomm-machine-learning-engineer-generative-ai-2","json_url":"https://alion.io/job/qualcomm-machine-learning-engineer-generative-ai-2.json","meta":{"generated_at":"2026-09-24T23:44:53Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":1913,"day_limit":5000,"remaining_today":3087,"minute_limit":60,"resets_at":"2026-09-25T00:00:00Z"}}}