{"id":2130682,"url":"https://alion.io/job/cognizant-staff-machine-learning-infrastructure-engineer","title":"Staff Machine Learning Infrastructure Engineer","company":{"id":85,"name":"Cognizant","domain":"cognizant.com","url":"https://alion.io/company/cognizant","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Cognizant Careers","truth_index":{"grade":"B","score":83,"open_postings":99,"ghost_share":0,"stale_share":0.869,"repost_share":0,"time_to_fill_p50_days":21,"computed_at":"2026-10-19T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":130000,"max":145000,"currency":"USD","period":"year","gross":null,"usd_annual":145000},"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Feature Store","optional":false},{"name":"Machine Learning","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Rest-Assured","optional":false},{"name":"Spark","optional":false},{"name":"TensorFlow","optional":false},{"name":"TorchServe","optional":false},{"name":"Triton","optional":false}],"status":"live","first_seen_at":"2026-10-05T10:01:49Z","employer_posted_date":"2026-10-09","last_verified_at":"2026-10-20T01:59:19Z","board_verified":true,"closed_at":null,"days_open":14,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":14},"description":"About the role\nAs a Staff Machine Learning Infrastructure Engineer, you will make an impact by architecting and advancing scalable machine learning infrastructure that enables the development, deployment, and operation of ML models at enterprise scale. You will be a valued member of the ML Platform Engineering team and work collaboratively with data scientists, machine learning engineers, platform engineers, and cross-functional technology stakeholders to deliver reliable, high-performance ML systems.\nIn this role, you will:\nArchitect and evolve end-to-end machine learning platforms supporting data processing, feature management, training, and model serving.\nDesign and implement scalable infrastructure that enables efficient development, deployment, and operation of ML workloads.\nDrive technical strategy, standards, and best practices for machine learning infrastructure, automation, and platform reliability.\nLead the design of real-time and batch inference solutions that support high-volume production workloads.\nMentor engineers, lead technical reviews, and partner with data science teams to accelerate ML adoption and innovation across the organization.\nWork model\nAt Cognizant, we strive to provide flexibility wherever possible, and we are here to support a healthy work-life balance through our various well-being programs. Based on this role’s business requirements, this is an onsite position requiring 5 days per week in a client or Cognizant office in Sunnyvale, CA.\nThe working arrangements for this role are accurate as of the date of posting. This may change based on the project you’re engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.\nWhat you need to have to be considered\n10+ years of software engineering experience, including 5+ years focused on machine learning infrastructure, MLOps, or platform engineering.\nDeep expertise designing and operating distributed systems and large-scale data processing platforms.\nProven experience building and supporting production ML platforms that power mission-critical business applications.\nHands-on experience with technologies such as Apache Spark, Apache Beam, feature stores, and large-scale data pipelines.\nStrong knowledge of ML serving and inference platforms, including TorchServe, TensorFlow Serving, Triton, or similar technologies.\nExperience with containerization, orchestration platforms, cloud-native architectures, and infrastructure automation.\nDemonstrated success leading complex technical initiatives and influencing architecture decisions across engineering organizations.\nThese will help you stand out\nExperience designing and optimizing GPU-based infrastructure for machine learning workloads.\nBackground in high-performance computing environments.\nExpertise in ML observability, monitoring, reliability engineering, and operational excellence.\nContributions to open-source machine learning infrastructure, platform engineering, or MLOps projects.\nMaster’s degree in computer science, Engineering, or a related technical field.\nExperience supporting security, governance, and compliance requirements within ML ecosystems.\nWe're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role.\nSalary and Other Compensation:\nApplications will be accepted until October 25, 2026\nThe annual salary for this position is between $ 130,000 - $ 145,000 depending on experience and other qualifications of the successful candidate.\nThis position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.\nBenefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:\nMedical/Dental/Vision/Life Insurance\n\nPaid holidays plus Paid Time Off\n\n401(k) plan and contributions\n\nLong-term/Short-term Disability\n\nPaid Parental Leave\n\nEmployee Stock Purchase Plan\n\nDisclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. 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