Mejorar el desempeño de Ruido, Vibración y Dureza (NVH) en vehículos de producción, enfocándose en los atributos críticos de Road Noise, Body Structure, Isolation y Ride Comfort. El proyecto busca asegurar que los vehículos cumplan con los estándares de calidad y confort establecidos por el fabricante (ej.: Nissan) y las regulaciones gubernamentales, mediante pruebas estandarizadas, análisis de datos y propuestas de mejora técnica.

At Jabil (NYSE: JBL), we are proud to be a trusted partner for the world's top brands, offering comprehensive engineering, supply chain, and manufacturing solutions. With 60 years of experience across industries and a vast network of over 100 sites worldwide, Jabil combines global reach with local expertise to deliver both scalable and customized solutions. Our commitment extends beyond business success as we strive to build sustainable processes that minimize environmental impact and foster vibrant and diverse communities around the globe. SUMMARY The Lead PLM Configuration Engineer is an individual contributor responsible for disciplined configuration control and lifecycle governance of all CAD models, BOMs, and technical documentation within the PLM system. This role acts as the system authority ensuring data integrity, traceability and alignment across mechanical, electrical, and documentation domains throughout concept, NPI, production and sustaining phases. The position owns revision management, baselining, effectiveness, and ECR/ECN workflows, preventing data divergence while enabling scalable, repeatable engineering operations. The role is critical to supporting customer audits, compliance requirements, and product lifecycle traceability in complex, configuration driven product environments. Job Title: Lead PLM Configuration Engineer Organization: Data Center Infrastructure Team Location: Austin, TX - or Remote* *Requires up to 25% domestic and/or international travel (rare) KEY RESPONSIBILITIES PLM Ownership & Configuration Control - Own and execute end-to-end configuration control for CAD models, BOMs and technical documentation within the PLM system. - Act as the authoritative source and gatekeeper for released product data, preventing uncontrolled changes, orphaned revisions or data misalignment. - Ensure consistent application of revision rules, lifecycle states and release criteria across all engineering artifacts. - Maintain tight synchronization between CAD structures, EBOMs and released documentation. Engineering Change & Lifecycle Execution - Own and enforce ECR/ECN workflows, ensuring changes are properly justified, reviewed, approved and traceable. - Manage effectivity, as‑built vs. as‑designed alignment and revision applicability across programs and product variants. - Support rapid yet disciplined execution of engineering changes without compromising configuration integrity or audit readiness. - Ensure historical traceability of changes across the full product lifecycle. Librarian & Data Governance Functions - Perform PLM librarian functions, including structure management, metadata accuracy, access control and data hygiene. - Define and enforce naming conventions, numbering schemes and classification rules. - Identify and resolve configuration discrepancies, duplicate records and data integrity risks. - Serve as escalation point for complex configuration or release conflicts. Cross‑Domain Alignment - Partner closely with mechanical and electrical CAD engineers to ensure alignment between designs, BOMs and documentation at release. - Work with manufacturing, quality, supply chain and production teams to ensure released data supports downstream execution and traceability. - Participate as a technical contributor in design reviews, release readiness reviews, and change control boards. Audit Readiness & Traceability - Ensure PLM data structures support customer audits, compliance reviews and internal governance requirements. - Provide traceable, auditable records linking requirements, designs, changes and released configurations. - Support customer and third-party audits by producing accurate configuration histories and impact assessments. Required Qualifications - Bachelor’s degree in Engineering, Manufacturing, or equivalent professional experience. - 8+ years of hands-on experience in PLM, configuration management or product data governance in complex engineering environments. - Deep working knowledge of PLM systems (e.g., Windchill, Teamcenter, Agile, etc.), release workflows and engineering change processes. - Demonstrated experience enforcing configuration discipline across multi-domain engineering teams. - Strong understanding of CAD / BOM /document relationships and lifecycle alignment. - Ability to operate independently as a senior technical authority. Preferred Experience - Experience supporting complex electromechanical systems (e.g., cooling systems, CDUs, industrial infrastructure). - Background in NPI and sustaining engineering environments with frequent design change. - Experience supporting customer, regulatory or quality audits. - Familiarity with configuration challenges associated with product variants, options and regional differences. Core Competencies - Senior level hands on PLM execution - Relentless discipline around configuration integrity - High attention to detail and procedural rigor - Strong systems thinking across mechanical, electrical and documentation domains - Ability to enable speed without sacrificing governance - Independent technical ownership without managerial responsibility ​ About the Data Center Infrastructure (DCI) Team: The DCI team consists of technical subject matter experts who specialize in end-to-end large scale physical infrastructure that powers and enables modern data centers. This includes power distribution systems such as transformers, substations, generators, switchgear, switch panels, busways, ATS units, EDPM, BMS systems, and control panels, as well as cooling solutions ranging from traditional evaporative and indirect cooling systems to emerging liquid cooling technologies including chillers, heat exchangers, CDUs, pumps, and secondary fluid networks. The team also addresses the mechanical structures that house these systems - hot aisle containment, steel enclosures, blanking panels, cable trays, and fiber and networking infrastructure. The DCI team operates as a cross-industry center of excellence, partnering primarily with various cloud providers across the industry. Team members function as deeply technical subject matter experts who engage directly with customers and supply chain partners to assess requirements, identify challenges, and design infrastructure solutions end-to-end. The ideal contributor brings engineering-level expertise in either power or cooling disciplines, a working knowledge of the full infrastructure dependency chain, and the ability to translate that expertise into clear recommendations and collaborative problem-solving with both technical and business stakeholders. The pay range for this role is $105,100 - $189,200. Job-related, non-discriminatory factors used to determine the actual offered rate include qualifications and experience, geographic location, education, external market data, and consideration of internal equity. The anticipated close date of this job requisition is: May 31, 2026. As part of the total rewards package, this position is eligible for a short-term incentive based on performance. In addition, Jabil offers benefits to enhance your health, wealth, and resilient self. These include medical, dental, and vision insurance plans; paid time off accruing at a rate of 3.07 hours during your first year of employment; 4 weeks of paid parental leave; in 2026, 11 company-paid holidays (9 fixed holidays and 2 optional floating holidays), subject to change yearly; 401(k) retirement plan; and employee stock purchase plan. BE AWARE OF FRAUD: When applying for a job at Jabil you will be contacted via correspondence through our official job portal with a jabil.com e-mail address; direct phone call from a member of the Jabil team; or direct e-mail with a jabil.com e-mail address. Jabil does not request payments for interviews or at any other point during the hiring process. Jabil will not ask for your personal identifying information such as a social security number, birth certificate, financial institution, driver’s license number or passport information over the phone or via e-mail. If you believe you are a victim of identity theft, contact the Federal Bureau of Investigations internet crime hotline (www.ic3.gov), the Federal Trade Commission identity theft hotline (www.identitytheft.gov) and/or your local police department. Any scam job listings should be reported to whatever website it was posted in. Jabil, including its subsidiaries, is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, age, disability, genetic information, veteran status, or any other characteristic protected by law. Accessibility Accommodation If you are a qualified individual with a disability, you have the right to request a reasonable accommodation if you are unable or limited in your ability to use or access Jabil.com/Careers site as a result of your disability. You can request a reasonable accommodation by sending an e-mail to Always_Accessible@Jabil.com or calling 727-803-7988 with the nature of your request and contact information. Please do not direct any other general employment related questions to this e-mail or phone number. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to. #whereyoubelong #AWorldofPossibilities

Job Description: Strategic Imperative: The Principal ML Engineer will lead the architecture, design, and evolution of machine learning across our Performance Marketing domain. This role is for a senior technical leader with deep experience in AdTech / MarTech, especially in ranking, rewards, ROAS / LTV modeling, and optimization systems. The role will define the ML vision for the domain, guide model and data architecture, make key decisions on MLOps, modelling and experimentation, tooling, and scalable system design, and mentor a growing team of engineers and data scientists. Just as importantly, you will help build an AI-first engineering mindset across the ML organization, using AI where it meaningfully improves speed, quality, insight generation, and decision-making. Prodege: A cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Blackstone in Q1 2026, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences. As an organization, we go the extra mile to “Create Rewarding Moments” every day for our partners, consumers, and team. Come join us today! Primary Objectives: - Advanced Level ML Architecture & Technical Direction - End-to-End Machine Learning Systems Delivery - Productionization, Reliability & Lifecycle Management - Advanced Experimentation, Monitoring & Model Performance Optimization - Scalable AI Platform, Feature & Inference Enablement - Cross-Functional Technical Leadership & Business Partnership - Engineering Standards, Mentorship & AI Capability Enablement Qualifications - To perform this job successfully, an individual must be able to perform each job duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Detailed Job Duties: (typical monthly, weekly, daily tasks which support the primary objectives) - Define the machine learning strategy and technical vision for Performance Marketing - Lead the development of sophisticated models, from selecting loss functions and architectures to fine-tuning hyperparameters and managing deployments. - Build "Version 0" of critical systems, writing production-quality code to prove out new modeling approaches before scaling them across the team. - Architect and evolve ML systems across areas such as: - ranking and recommendation - rewards optimization - ROAS / LTV prediction - campaign and offer optimization - experimentation and decisioning systems - Design scalable ML architectures across offline training, online inference, feature generation, feedback loops, and model monitoring - Partner closely with the Data team to define the right data models, data contracts, feature pipelines, training datasets, and measurement foundations needed for reliable ML systems - Establish the right experimentation framework for ML models, including offline evaluation, online testing, A/B experimentation, KPI design, and post-launch performance measurement - Lead by example through active code contributions and deep-dive PR reviews, ensuring high standards for model performance and system reliability. - Make key decisions on MLOps, tooling, infrastructure, model serving, observability, and platform architecture - Drive an AI-first mindset within the ML organization by using AI to accelerate research, prototyping, feature engineering, experimentation analysis, documentation, model debugging, and developer productivity where it makes sense - Guide the team on how to build systems that are scalable, reliable, cost-aware, and production-ready - Partner with Product, Engineering, Analytics, and business teams to translate commercial goals into ML roadmaps - Mentor ML engineers and data scientists, helping raise the bar on model quality, engineering rigor, and technical judgment - Set best practices for model validation, monitoring, retraining, drift detection, explainability, and governance The MUST Haves: (ex: job cannot be done without these skills, education, experience, certifications, licenses) - Bachelor’s degree in a relevant technical field, or equivalent practical experience. - Eight or more (8+) years of experience in software engineering, machine learning engineering, MLOps, or a related field. - Five or more (5+) years of experience building, deploying, and supporting production machine learning systems at scale. - Deep experience in Machine Learning engineering in AdTech, MarTech, Growth, Performance Marketing, or adjacent domains - Strong background in: - Ranking - Recommendation - rewards / incentives - ROAS / LTV prediction - personalization / optimization systems - Proven experience designing and shipping production ML systems at scale - Strong understanding of: - feature engineering and feature stores - offline / online ML architecture - model serving patterns - experimentation frameworks for ML systems - A/B testing and measurement design - MLOps, monitoring, retraining, and model governance - Experience with Counterfactual Reasoning, Causal Inference, or Uplift Modeling. - Experience working closely with Data Engineering / BI / Analytics teams to ensure clean, scalable, and trustworthy data foundations for ML - Strong system design skills with ability to make the right tradeoffs across performance, reliability, scalability, and cost - Ability to guide teams toward an AI-first way of working, using AI as a force multiplier for model development, experimentation, and engineering productivity - Strong judgment around where AI adds leverage and where human review, rigor, and validation remain essential - Ability to lead technically across teams and influence architecture decisions without direct authority - Strong mentoring and leadership skills; able to guide junior engineers and shape a strong ML engineering culture The Nice to Haves: (ex: preferred additional skills, education, experience, certifications, licenses) - Master’s degree or PhD in AI, Machine Learning, or a quantitative field. - Experience in rewards, offer ecosystems, customer value optimization, or monetization platforms - Experience with streaming or near-real-time decisioning systems - Experience building ML platforms or shared experimentation infrastructure - Familiarity with modern AI-assisted / AI-first development practices across engineering and data science teams Pay Transparency: The anticipated base salary range for this position is $300,000 to $375,000. The final salary offered to a successful candidate will be dependent on several factors that may include, but are not limited to; the type and length of experience within the job, type and length of experience within the industry, the type and length of knowledge and skills for the position, education, training, etc. Prodege is a multi-state employer and final compensation within this range could be impacted by work location. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Prodege Benefits: Prodege offers a comprehensive benefits package to US Full-time employees including medical, dental, vision, STD, LTD and basic life insurance. Employees receive flexible PTO, as well as paid sick leave prorated based on hire date. US Employees have eight paid holidays throughout the calendar year. Employees receive an option to purchase shares of Company stock commensurate with their position, which vests over four years. Equal Employment Opportunity Statement At Prodege, we are committed to creating a diverse and inclusive environment. We are proud to be an Equal Opportunity Employer and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic protected by law. We encourage individuals of all backgrounds to apply. FCIHO Employers will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of FCIHO.

• Under direct supervision and working with experienced staff, the successful candidate will complete substation engineering designs and the generation of construction drawing plans and details, schematic and wiring diagrams, technical calculations, models, exhibits, and reports. • Utilize CAD software to develop plans, sections, schematics, details, wiring, and BOM sheets for construction drawing sets. • Ability to work as a team player, take direction, and interact well with others while working in remote, hybrid, or office environments. • Self-starter with strong internal drive and integrity that can work well individually and with team members. • Individual contributor expected to complete assigned work from senior staff, perform self-checks of work produced and continue advancing technical knowledge and professional licensure.