{"id":1672107,"url":"https://alion.io/job/qualcomm-machine-learning-engineer-2","title":"Machine Learning Engineer","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":78,"open_postings":1016,"ghost_share":0.142,"stale_share":0.097,"repost_share":0.402,"time_to_fill_p50_days":75,"computed_at":"2026-10-03T05:45:00Z"}},"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":122800,"max":184200,"currency":"USD","period":"year","gross":null,"usd_annual":184200},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"ONNX","optional":false},{"name":"Quantization","optional":false},{"name":"vLLM","optional":false},{"name":"AI Agents","optional":true},{"name":"C++","optional":true},{"name":"CI/CD","optional":true},{"name":"Docker","optional":true},{"name":"Embeddings","optional":true},{"name":"Knowledge Distillation","optional":true},{"name":"Kubernetes","optional":true},{"name":"KV Cache","optional":true},{"name":"Model Distillation","optional":true},{"name":"Multimodal AI","optional":true},{"name":"OpenSearch","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"PyTorch C++","optional":true},{"name":"Qdrant","optional":true},{"name":"RAG","optional":true},{"name":"Rest-Assured","optional":true},{"name":"Rust","optional":true},{"name":"TensorFlow","optional":true},{"name":"TensorFlow C++","optional":true},{"name":"Transformers","optional":true}],"status":"live","first_seen_at":"2026-09-25T00:00:00Z","employer_posted_date":"2026-09-30","last_verified_at":"2026-10-04T02:48:01Z","board_verified":true,"closed_at":null,"days_open":9,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":9},"description":"Company:\nQualcomm IncorporatedJob Area:\nEngineering Group, Engineering Group > Machine Learning EngineeringGeneral Summary:\nWe are seeking a highly skilled Core ML Engineer to design, develop, and optimize machine learning systems that power next-generation AI platforms and applications. This role focuses on model development, inference optimization, and scalable ML infrastructure, enabling production-grade AI capabilities across enterprise systems.\nThe ideal candidate combines strong software engineering fundamentals with deep ML expertise, and thrives in building robust, high-performance systems at scale.\nKey Responsibilities\nCore ML System DevelopmentDesign and implement machine learning models and pipelines for production use\nBuild scalable training → evaluation → deployment workflows\nDevelop reusable ML components, libraries, and frameworks\n\nInference & Performance OptimizationOptimize model inference for latency, throughput, and cost\nImplement advanced techniques such as caching, quantization, batching, and routing\nBenchmark and profile models across diverse workloads and hardware environments\n\n Model Integration & DeploymentIntegrate ML/LLM models into APIs, microservices, and applications\nBuild and maintain model-serving infrastructure (e.g., vLLM, ONNX, custom runtimes)\nCollaborate with platform and infrastructure teams for scalable deployment\n\nData & Pipeline EngineeringDesign data pipelines for ingestion, preprocessing, feature engineering, and validation\nImprove data quality and model reliability through systematic evaluation\n\nCross-functional CollaborationPartner with product, platform, and hardware teams to deliver end-to-end ML solutions\nParticipate in design reviews and contribute to system architecture decisions\n\nMinimum Qualifications:\n• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.Preferred Qualifications\nStrong programming skills in Python and at least one systems language (C++/Rust/Go)\nSolid understanding of:\nMachine learning fundamentals (supervised, unsupervised, deep learning)\nTransformer architectures / LLMs\nModel evaluation and debugging\nExperience with:\nML frameworks (PyTorch, TensorFlow)\nModel deployment and serving systems\nBuilding scalable software and APIs\nExperience with:\nLarge Language Models (LLMs), multimodal models, or generative AI\nRetrieval systems and RAG pipelines\nDistributed computing and GPU/accelerator environments including model serving and efficient cache/state management (e.g. KV cache, embeddings) across disaggregated systems\nKubernetes, Docker, and CI/CD pipelines\nAgentic and multi-step AI workflows, tool integration, orchestration, and multi-component pipelines\nKnowledge of:\nModel optimization techniques (quantization, distillation, caching)\nVector databases and search systems (OpenSearch, Qdrant, etc.)\nCost-aware system design - model routing (small vs. large models), dynamic batching, and caching strategies\nThis is an office-based position located in San Diego, CA and is expected to comply with the company's onsite work policy.\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$122,800.00 - $184,200.00The 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":5897,"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","Autonomous Driving","Energy Efficiency","Car Electronics"],"lifecycle":[{"event":"open","at":"2026-10-02T07:04:59Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 55 · green card filings: 6","filings_12m":55,"filings_prev_12m":87,"green_card_filings_12m":6,"median_offered_wage_usd":122008,"route":null,"cap_exempt":false,"checked_at":"2026-10-03T21:08:04+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":25}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":8,"expected_fill_days":75,"reasons":["conf:8","velocity","win:early","comp:brand"],"computed_at":"2026-10-03T05:45:00Z"},"pay":{"stated_usd_annual":184200,"is_top_pay":false},"html_url":"https://alion.io/job/qualcomm-machine-learning-engineer-2","json_url":"https://alion.io/job/qualcomm-machine-learning-engineer-2.json","meta":{"generated_at":"2026-10-04T02:59:01Z","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":4495,"day_limit":5000,"remaining_today":505,"minute_limit":60,"resets_at":"2026-10-05T00:00:00Z"}}}