A/AI Research Engineer Stf - E4

Requisition ID: 8715ERP Eligible?: YesERP amount: $5,000Relocation: NoType: ExemptShift: 1Clearance Prior to Start: NoneFinal Clearance: NonePay Transparency: $135,700.00 - $251,900.00Experience Level: Experienced ProfessionalFT/PT/Casual: FullTimeDepartment: Enterprise Business ServicesBusiness Unit: Enterprise Business ServicesStandard Job DescriptionFocuses on research & development of technologies that enable and advance semi and fully autonomous systems for both defense and commercial customers. Serves as the algorithm expert with up-to-date knowledge on modern AI research and may be involved in the inception of ideas and drive the development cycles from research to test of prototypes for a major project or component of a major project.Researches and discovers improvements to machine learning and robotic algorithms; Drives advancements in techniques used in signal processing, computer vision (CV), and control systems; Develops AI algorithms for mission systems; Applies latest research on AI algorithms and trains machine learning / deep learning models to solve a variety of problems; Investigates and applies the latest machine learning and deep learning techniques; Optimizes the performance of AI algorithms, applications, and platforms; Develops and documents algorithm and implementation requirements; Develops prototypes that will enable autonomous functionality in LM products and platforms; Interfaces with other teams involved the development lifecycle for perception, mission and motion planning, simulation and modeling, testing, etc.The Astris AI Sales Engineer serves as the technical backbone of our AI Factory go-to-market motion. This role owns the demo environments, proof-of-concept architectures, and technical narrative that show prospective enterprise customers what AI Factory platform — can do. It combines hands-on AI/ML engineering skill with strong presentation ability to support Account Executives across the full commercial sales cycle, from first technical discovery call through proof-of-concept and close.Demo & Technical Asset DevelopmentBuild and maintain reusable MLOps demo environments on Panel covering the full model lifecycle: experiment tracking, versioning, CI/CD for ML, deployment, and production monitoringDevelop industry-specific demo narratives and datasets (predictive maintenance, fraud detection, supply chain forecasting, and similar) that map Panel's capabilities to a prospect's actual workflowsMaintain demo infrastructure, including containerized and Kubernetes-based environments, so demos run reliably across customer meetings, trade shows, and remote sessionsBuild reusable technical assets: reference architectures, ROI calculators, solution briefs, and competitive comparison sheetsCustomer Engagement SupportPartner with Account Executives throughout the commercial sales cycle — qualification through closeLead technical discovery sessions to understand a prospect's existing infrastructure, data environment, team structure, and integration constraintsDeliver customized demonstrations and technical presentations to audiences ranging from data scientists and ML engineers to CTO/CIO-level executivesRespond to RFIs/RFPs with accurate technical content and MLOps-specific competitive positioningBuild trusted-advisor relationships with customer technical stakeholders and support technical handoffs to Customer Success Engineers and Solution Architects once a deal closesTechnical Enablement & CollaborationMaintain deep expertise in Panel and general MLOps best practices (model versioning, experiment tracking, CI/CD for ML, monitoring, governance)Stay current on the broader MLOps and Kubernetes ecosystem (Kubeflow, MLflow, KServe, Ray, Argo, and similar) to keep demos and competitive positioning sharpCollaborate with Product and Engineering to feed customer feedback and market signal into the Panel roadmapSupport partner-channel enablement (ISVs, SIs, cloud partners) with MLOps-focused technical training and co-selling assetsBasic Qualifications5–9 years in Sales Engineering, Solutions Engineering, Pre-Sales Technical Consulting, or a hands-on ML engineering / MLOps roleWorking proficiency in Python and at least one ML framework (PyTorch, TensorFlow, scikit-learn, or similar)Demonstrated ability to build and maintain demo or POC environments end-to-endDesired SkillsHands-on experience with MLOps platforms such as Astris AI Factory, MLflow, Kubeflow, Weights & Biases, or similar toolsWorking knowledge of generative AI / LLM concepts (RAG, agent frameworks)Experience selling into manufacturing, supply chain, financial services, or technology verticalsPractical experience with Kubernetes (deploying, debugging, or operating workloads) and containerizationPay InformationGeoZone Definition: GeoZones are geographic groupings created by Lockheed Martin to align compensation ranges with regional labor markets and cost-of-labor differences across the United States. Locations are assigned a Geo Zone based on the primary work location of the role.Full-time salary range (GEOZONE 1):$ - $ Includes metropolitan areas such as Sunnyvale CA; Pal Alto, CA; New York City metropolitan area; Newark, New Jersey; etc.Full-time salary range (GEOZONE 2): $ - $ Includes metropolitan areas such as Denver, CO; King of Prussia, PA; Stratford, CT; Moorestown, NJ; etc.Full-time salary range (GEOZONE 3): $ - $ Includes metropolitan areas such as Dallas–Fort Worth, TX; Orlando, FL; Grand Prairie, TX; Marietta, GA; etc.Full-time salary range (GEOZONE 4): $ - $ Includes metropolitan areas such as Camden, AR; Lexington, KY; Ocala, FL; Lufkin, TX; etc.At Lockheed Martin, we know mission success starts with taking care of our people. Our Total Rewards program is designed to attract top talent, support your well-being, and help you grow—both professionally and personally.The salary range for this position is aslisted on the requisition. Please note that the salary information listed is a general guideline only.Lockheed Martin considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/ training, key skills as well as market(work location) and business considerations when extending an offer. Benefits offered: Medical, Dental, Vision, Flexible work arrangements and schedules (e.g., 4x10), 401(k) match, Paid time off, Holidays, Parental Leave, EAP, Flexible Spending Accounts, Education Assistance, Life Insurance, Short-Term Disability, and Long-Term Disability.Annual short-term and/or long-term incentive compensation programs may be offered depending on the position. Payments under these annual programs are not guaranteed and can vary from year to year and are tied to a range of performance metrics.For (Washington state applicants only) Non-represented full-time employees: accrue at least 10 hours per month of Paid Time Off (PTO) to be used for incidental absences and other reasons; receive at least 90 hours for holidays. Represented full time employees accrue 6.67 hours of Vacation per month; accrue up to 52 hours of sick leave annually; receive at least 96 hours for holidays. PTO, Vacation, sick leave, and holiday hours are prorated based on start date during the calendar year.