{"id":4278960,"url":"https://alion.io/job/voyager-technologies-machine-learning-engineer","title":"Machine Learning Engineer","company":{"id":2451,"name":"Voyager Technologies","domain":"voyagertechnologies.com","url":"https://alion.io/company/voyager-technologies","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":85,"open_postings":5,"ghost_share":0,"stale_share":0.6,"repost_share":0,"time_to_fill_p50_days":49,"computed_at":"2026-11-12T10:38:37Z"}},"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":["El Segundo, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":120000,"max":280000,"currency":"USD","period":"year","gross":null,"usd_annual":280000},"salary_estimate":null,"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Computer Vision","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"C++","optional":true},{"name":"MATLAB","optional":true},{"name":"Multimodal AI","optional":true}],"status":"live","first_seen_at":"2026-11-13T14:06:42Z","employer_posted_date":"2026-11-13","last_verified_at":"2026-11-13T19:53:38Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Voyager is an innovative space, defense, and national security technology company committed to advancing and delivering transformative, mission-critical solutions. We tackle the most complex challenges to unlock new frontiers for human progress, fortify national security, and protect critical assets to lead in the race for technological and operational superiority from ground to space. \nForge the Future: Join Voyager Technologies \nThe future belongs to those who build it. At Voyager Technologies, we’re building technologies that protect lives, expand frontiers and prepare us for what’s next. And we’re doing that with people who are wired to solve, build, adapt and lead. These roles are not for the faint of heart. \nYou’ll help lay the foundation for humanity's future. Join a culture where innovation thrives, curiosity is rewarded, and impact is real. We’re a company of doers, thinkers and builders, united by purpose and grounded in reality. \nIf you want to put your skills to work where the stakes are real and the mission is bigger than any one person, forge the future with Voyager. \nThe Company is currently seeking Machine Learning Engineers who can develop cutting edge Deep Learning technologies applied to pressing problems in the domain of Computer Vision, Synthetic Aperture Radar (SAR), and Geospatial Exploitation. You will have considerable responsibility, and your role will have direct impact on relevant issues facing the United States government customers.\nThis posting stays open continuously. We hire machine learning engineers at several levels, from early career to senior staff, and review applications on a rolling basis. Your level and title are determined during the hiring process, based on your experience and the scope of your past work. See Levels We Hire For below.\nThis position is based in El Segundo, CA. If your experience aligns with our required qualifications and you are inspired by our mission, we’d like to connect. If you don’t see the right role right now, Join Our Talent Community and stay connected as we continue to build what’s next.\nIn this role, the essential functions are: \nWe hire at five levels; each row shows the typical experience and scope.\n\nTitle\n\nTypical experience\n\nScope\n\nMachine Learning Engineer I\n\n0-2 years\n\nImplements models and ML pipelines under guidance. Usually holds a BS or MS and may have internship or research experience.\n\nMachine Learning Engineer II\n\n2-5 years\n\nIndependently develops and deploys ML solutions. Can take an ML problem from requirements through implementation, including production deployment, model monitoring, feature engineering and experimentation.\n\nSenior Machine Learning Engineer\n\n5-8 years\n\nOwns complex ML systems and technical projects. Makes architecture decisions, mentors junior engineers, and works closely with product, data and platform teams.\n\nStaff Machine Learning Engineer\n\n8-12+ years\n\nProvides technical leadership across teams and systems, beyond simply owning larger individual projects. Defines architecture and technical direction across multiple teams and influences engineering standards and ML strategy.\n\nSenior Staff Machine Learning Engineer\n\n12-15+ years\n\nSets organization-wide technical strategy and architecture. Responsible for very large technical problems and/or company-wide ML architecture and strategy.\n\nAt every level, you will:\nResearch, conceive, design, prototype and/or implement advanced Deep Neural Network Architectures as well as other relevant Machine Learning models.\nApply deep learning algorithms to train neural networks for object detection and classification.\nDevelop domain-aware pre-processing algorithms, and other methods to increase model generalization.\nApply signal pre-processing techniques on SAR data.\nCreate physics simulations of various phenomenologies and develop methods to account for bias between simulated and real-world data.\nDevelop appropriate objective functions and sound performance assessment plans.\nPresent work at meetings and conferences.\nDevelop and deliver production-quality code (mainly Python).\nAs you move up in level, responsibilities build on those above:\nMachine Learning Engineer II and above: independently take machine learning problems from requirements through implementation, including production deployment, model monitoring, feature engineering and experimentation.\nSenior Machine Learning Engineer and above: own complex machine learning systems and technical projects, make architecture decisions, mentor junior engineers, and work closely with product, data and platform teams.\nStaff Machine Learning Engineer and above: provide technical leadership across teams and systems, define architecture and technical direction across multiple teams, and influence engineering standards and ML strategy.\nSenior Staff Machine Learning Engineer: set organization-wide technical strategy and architecture, and own very large technical problems and/or company-wide ML architecture and strategy.\nIf your experience aligns with our basic qualifications and you are inspired by our mission, we’d like to connect. If you don’t see the right role right now, Join Our Talent Communityand stay connected as we continue to build what’s next. \nQualifications build by level: each level includes everything from the level before it, plus the items listed. Years shown are years of applicable experience.\nMachine Learning Engineer I (0-2 years)\nBachelor’s degree in engineering or a related field.\nMachine Learning Engineer II (2-5 years): all Machine Learning Engineer I qualifications, plus:\nExperience independently taking an ML problem from requirements through implementation.\nExperience with production deployment, model monitoring, feature engineering and experimentation.\nSenior Machine Learning Engineer (5-8 years): all Machine Learning Engineer II qualifications, plus:\nA record of owning complex ML systems and technical projects.\nExperience making architecture decisions and mentoring junior engineers.\nExperience partnering with product, data and platform teams.\nStaff Machine Learning Engineer (8-12+ years): all Senior Machine Learning Engineer qualifications, plus:\nA record of technical leadership across teams and systems, beyond owning larger individual projects.\nExperience defining architecture and technical direction across multiple teams.\nExperience influencing engineering standards and ML strategy.\nSenior Staff Machine Learning Engineer (12-15+ years): all Staff Machine Learning Engineer qualifications, plus:\nA record of setting organization-wide technical strategy and architecture.\nExperience owning very large technical problems and/or company-wide ML architecture and strategy.\nExperience developing or guiding advanced machine learning, signal-processing and exploitation algorithms, and leading technical efforts across organizational and disciplinary boundaries.\nAbility to evaluate unfamiliar sensors and datasets using first-principles reasoning.\nAbility to communicate complex technical concepts to expert and non-expert audiences, mentor senior technical staff, and operate effectively with limited direction.\n\nPreferred Qualifications:\nThese apply across all levels.\nMaster’s degree or PhD.\nStrong background in Machine Learning (preferably Deep Neural Networks).\nNeed to be flexible in a small business environment.\nFamiliarity with radar sensing phenomenology.\nOpen Source frameworks is a huge plus.\nAbility to program in multiple languages (Python, Matlab, C/C++).\nExperience connecting physics-based signal processing with machine learning, computer vision, or automated exploitation.\nExpertise in areas such as target detection and recognition, geolocation, or multimodal fusion.\nTravel, Physical and/or Government Mandated Requirements:\nAbility to obtain and maintain a US Government Security Clearance\nThe good faith base salary range for this role is $120,000 - $280,000 at the time of this posting. Where you fall within the range depends on your experience, skills, and location. This range reflects base salary only and does not include benefits or bonus/incentive. This range may be adjusted in the future.\nVoyager offers a highly competitive total compensation package designed to support the well-being, growth, and success of our employees. Employees benefit from a flexible and comprehensive rewards program that supports both professional and personal well-being. \nFlexible Time Off (FTO), empowering employees to take the time they need to recharge and maintain a healthy work-life balance\nComprehensive medical, dental, and vision coverage for employees and their families, with a significant portion of premiums covered by the company and many benefits paid at 100% for employees\nFlexible, affordable gym memberships with 12,700+ options nationwide, including 24 Hour Fitness, EoS Fitness, Crunch Fitness, Anytime Fitness, Blink Fitness, Chuze Fitness, and more! No long-term contracts and FREE on-demand workout videos before you enroll\n401(k) retirement plan with a 50% company match on contributions up to 8%, supporting long-term financial security\nCompany wellness programs that support physical and mental well-being\nAdditional voluntary benefits and employee support resources\nThe opportunity to work alongside a highly talented team in an innovative, mission-driven environment\nVoyager is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status, or other characteristics protected by law. \nTo conform to U.S. Government export regulations, including the International Traffic in Arms Regulations (ITAR) (22 CFR Parts 120-130) and the Export Administration Regulations (EAR) (15 CFR Parts 730-774), applicants for this position must be a U.S. Person: a US Citizen, a lawful permanent resident of the U.S., or a protected individual as defined by 8 U.S.C. § 1324b(a)(3). Applicants must be eligible to obtain any required export authorizations from the U.S. Department of State or the U.S. Department of Commerce. \nMinority/Female/Disabled/Veteran \nThe statements contained in this job description are intended to describe the general content and requirements for performance of this job. It is not intended to be an exhaustive list of all job duties, responsibilities, and requirements. This job description is not an employment agreement or contract. 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