{"id":738986,"url":"https://alion.io/job/cisco-systems-machine-learning-engineering-technical-leader-cx-ai","title":"Machine Learning Engineering Technical Leader - CX AI","company":{"id":90,"name":"Cisco Systems","domain":"cisco.com","url":"https://alion.io/company/cisco-systems","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":83,"open_postings":239,"ghost_share":0.046,"stale_share":0.498,"repost_share":0.092,"time_to_fill_p50_days":26,"computed_at":"2026-11-03T05:54:40Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Jose, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":256900,"max":383500,"currency":"USD","period":"year","gross":null,"usd_annual":383500},"salary_estimate":null,"experience_years_min":11,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"Fine-tuning","optional":false},{"name":"JAX","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Agentic Workflows","optional":true},{"name":"CI/CD","optional":true},{"name":"Knowledge Distillation","optional":true},{"name":"KV Cache","optional":true},{"name":"llama.cpp","optional":true},{"name":"LoRA","optional":true},{"name":"Model Distillation","optional":true},{"name":"OpenAI","optional":true},{"name":"PEFT","optional":true},{"name":"Quantization","optional":true},{"name":"RAG","optional":true},{"name":"SGLang","optional":true},{"name":"Speculative Decoding","optional":true},{"name":"TensorRT","optional":true},{"name":"TensorRT-LLM","optional":true},{"name":"Transfer Learning","optional":true},{"name":"Transformers","optional":true},{"name":"Triton","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-09-11T12:01:08Z","employer_posted_date":"2026-09-11","last_verified_at":"2026-11-04T02:43:20Z","board_verified":true,"closed_at":null,"days_open":53,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":53},"description":"The application window is expected to close on: 11/26/2026This is a Hybrid role requiring 3 days per week in the San Jose, CA office.\nMeet the Team\nCisco's CX AI Foundations team owns the foundational AI platform behind intelligent customer experiences across Cisco - the shared layer that application and agent teams across CX build on, in cloud, on-premises, and fully air-gapped customer environments.\nOur charter spans the platform end to end: the model and inference layer (including SLM specialization and the LLM-compatible API), evaluation systems for shipped AI behavior, agentic and orchestration infrastructure, foundational AI services and APIs, and the packaging and upgrade machinery that makes AI supportable in the field - including the on-prem AI appliance now shipping to customers. The portfolio is expanding as Cisco's AI footprint grows.\nThis is a small, deeply technical team with production commitments.\nYour Impact\nAs a senior hands-on technical leader in Cisco’s CX Engineering organization, you will architect, build, and deliver foundational, enterprise-scale AI services that power critical platform capabilities. Operating as a builder rather than a coordinator, you will own complex technical challenges end-to-end-driving model selection and fine-tuning, inference optimization, agentic infrastructure, multi-tenant API contracts, and air-gapped deployments across diverse compute targets. You will establish the benchmark for scientific rigor and statistical evaluation-treating regression gating, judge calibration, and drift detection as mandatory release criteria-while mentoring senior engineers through technical depth and influence rather than positional authority. In this role, you will bridge cutting-edge AI research with reliable production engineering, collaborating across product, security, and executive leadership to drive architectural roadmaps, uphold responsible AI governance, and champion engineering excellence across the organization.\nMinimum Qualifications:\nBachelor's degree with 11+ years of related experience, or Master's degree with 7+ years of related experience. \nMachine learning experience to include model development, training and adaptation, and evaluation.\nExperience with Python and modern ML frameworks such as PyTorch or JAX or similar. \nExperience taking machine learning work from research or prototype through to production. \nProduction experience in at least one foundational AI platform area - model serving and inference, evaluation systems for generative AI, agentic/orchestration infrastructure, or AI platform services and APIs. \nExperience leading full lifecycle projects. \nPreferred Qualifications:\nTechnical & Architectural Leadership\nProduction Platform Ownership: Track record architecting and operating shared AI/ML inference platforms and APIs consumed across multiple teams, including API contract design, versioning, and backward compatibility.\nIncubation to Delivery: Proven experience leading concurrent technical workstreams and navigating AI solutions from experimental incubation through to supported, enterprise-grade production products.\nEngineering Mentorship: Demonstrated success mentoring, coaching, and elevating senior engineers and applied researchers.\nApplied Machine Learning & Inference Systems Depth\nHigh-Performance Inference: Hands-on experience deploying and profiling LLM/SLM serving engines (vLLM, TensorRT-LLM, Triton, SGLang, llama.cpp) utilizing optimizations such as continuous batching, KV-cache management, quantization, and speculative decoding.\nModel Specialization & Adaptation: Deep expertise in fine-tuning, distillation, transfer learning, and PEFT/LoRA, as well as designing OpenAI-compatible interfaces over specialized models.\nRigorous Generative Evaluation: Experience building statistical evaluation frameworks for non-deterministic AI systems-including golden datasets, LLM-as-a-judge calibration, human-agreement metrics, regression gates, and drift detection.\nAgentic Architectures: Production experience designing multi-turn agentic workflows, autonomous tool integration, and advanced retrieval (RAG) architectures.\nEnterprise, Edge & MLOps Infrastructure\nHybrid & Air-Gapped Deployments: Experience packaging and delivering AI services into cloud, customer-managed, air-gapped, and resource-constrained compute environments (CPU, NPU, small GPU) with strict upgrade safety and supportability.\nProduction MLOps: Hands-on foundation in modern AI infrastructure practices, including automated CI/CD pipelines for models, model registries, experiment tracking, and real-time telemetry/observability.\nSecurity & Governance: Comprehensive understanding of enterprise security reviews, data boundary isolation, privacy controls, and responsible AI compliance.\nThought Leadership & External Influence\nIndustry Impact: Record of external technical contributions via patents, peer-reviewed publications, open-source AI projects, or conference presentations.\nWhy Cisco?\nAt Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era - and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.\nFueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.\nWe are Cisco, and our power starts with you.\nMessage to applicants applying to work in the U.S. and/or Canada:\nThe starting salary range posted for this position is $256,900.00 to $333,400.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process.\nU.S. employees are offered benefits, subject to Cisco’s plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time.\nU.S. employees are eligible for paid time away as described below, subject to Cisco’s policies:\n10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees\n\n1 paid day off for employee’s birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco\n\nNon-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees\n\nExempt employees participate in Cisco’s flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)\n\n80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next\n\nAdditional paid time away may be requested to deal with critical or emergency issues for family members\n\nOptional 10 paid days per full calendar year to volunteer\n\nFor non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco’s policies.\nEmployees on sales plans earn performance-based incentive pay on top of their base salary, which is split between quota and non-quota components, subject to the applicable Cisco plan. For quota-based incentive pay, Cisco typically pays as follows:\n.75% of incentive target for each 1% of revenue attainment up to 50% of quota;\n\n1.5% of incentive target for each 1% of attainment between 50% and 75%;\n\n1% of incentive target for each 1% of attainment between 75% and 100%; and\n\nOnce performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation.\n\nFor non-quota-based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid.\nThe applicable full salary ranges for this position, by specific state, are listed below:\nNew York City Metro Area:\n$256,900.00 - $383,500.00Non-Metro New York state & Washington state:\n$234,400.00 - $341,100.00* For quota-based sales roles on Cisco’s sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined.\n** Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements.","description_format":"text","description_chars":9499,"description_truncated":false,"requirements":{"experience_years_min":11,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Annual bonuses","Equity","Life insurance","Parental leave","Restricted stock 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