{"id":2993484,"url":"https://alion.io/job/apple-rf-systems-architect-control-algorithms-2","title":"RF Systems Architect - Control Algorithms","company":{"id":12,"name":"Apple","domain":"apple.com","url":"https://alion.io/company/apple","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Apple Jobs","truth_index":{"grade":"A","score":90,"open_postings":824,"ghost_share":0,"stale_share":0.214,"repost_share":0.006,"time_to_fill_p50_days":122,"computed_at":"2026-11-11T05:49:22Z"}},"role":"Hardware","role_family":"Hardware","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":["Waltham, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":237000,"max_usd":432000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":527},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"MATLAB","optional":false},{"name":"Python","optional":false},{"name":"Machine Learning","optional":true}],"status":"live","first_seen_at":"2026-04-15T16:27:04Z","employer_posted_date":"2026-11-11","last_verified_at":"2026-11-11T16:28:00Z","board_verified":true,"closed_at":null,"days_open":210,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":210},"description":"At Apple, our work is dedicated to creating products that connect and enrich people's lives. The Cellular RF Systems Engineering team sits at the very core of that mission, defining the wireless technologies that enable seamless experiences for hundreds of millions of users worldwide.\nWe are looking for a passionate engineer to design the intelligent control algorithms that orchestrate our RF Front-End hardware. By translating complex 5G and 6G use cases into optimized RF hardware control strategies, you will directly balance RF performance, power consumption, and thermal limits to deliver a world-class wireless experience.\nDescription\nIn this role, you will be responsible for the optimal interaction between our RF transceivers and RF Front-End modules. Your primary focus will be breaking down advanced cellular capabilities, such as SRS antenna switching, MIMO and Multi-SIM, into clear system requirements and concrete control flows. This is a highly collaborative role where you will partner with diverse engineering teams across the entire cellular stack to bring these cutting-edge concepts into our next-generation cellular products.\nMinimum Qualifications\nBS and 10+ years of relevant industry experience required.\nDeep understanding of 5G NR and LTE-Advanced physical layer procedures, particularly involving MIMO, SRS, and carrier aggregation.\nStrong working knowledge of RF Front-End architectures and the system-level impact of components like PAs, LNAs, filters, and switches.\nProven track record of developing control algorithms, state machines, or system-level models for complex hardware.\nProficiency in Python, MATLAB, or C/C++ for data analysis, system modeling, and algorithm development.\nAbility to critically analyze complex trade-offs, such as routing flexibility versus insertion loss, or throughput versus battery life.\nStrong communication skills with a proven ability to work across diverse, cross-functional teams to solve highly complex, multi-disciplinary problems.\nPreferred Qualifications\nMS or PhD in Electrical Engineering, Physics, or a related field.\n3+ years of industry experience in RF systems or transceiver architectures with a focus on advanced cellular communication topics.\n5+ years of experience in RF systems engineering or 10+ years in communications circuit design.\nHands-on experience with RF filter technologies, power amplifier characterization, and Front-End module integration.\nExpertise in designing and simulating analog and digital signal processing paths.\nExperience applying Machine Learning or AI techniques to solve system-level optimization problems.\nHistory of successfully balancing cutting-edge hardware innovation with the practical constraints of high-volume 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