• develop field instrumentation datasheets, instrument lists, and instrument rack lists, and specifications, instrument installation details that relate to the BWRX-300 SMR Instrumentation Design scope • focus on the design integration of field pipe mount and rack mounted instrumentation with GEV control hardware systems • collaborate with other engineers and technical leads to develop innovative designs • execute projects of varying complexity in different project phases under the guidance of senior engineers and TLs within the team • own & execute tasks from different workstreams that relates to BWRX-300 instrumentation design engineering • responsible for developing innovative engineering solutions for BWRX-300 process instrumentation and meeting customer’s Critical-to-Quality (CTQ) requirements and GE Vernova’s design guidelines • develop detailed instrumentation schematic, wiring and cable block arrangement drawings/BOM to support process or mechanical system upgrade or modifications anticipated on a project • interpret the scope of the project and develop or review instrument datasheets, piping & instrumentation diagrams (P&ID) and instrumentation racks list, deploying I&C design principles to improve the overall system performance • develop or strongly support standardization and/or cost-out efforts to improve the competitiveness of GE Vernova’s product and service offerings • contribute to quarterly, semi-annual and annual team priorities and initiatives • interact effectively with other GE Vernova customers and suppliers, as well as with internal GEV functions

• responsible for Technical Leadership of configuration management aspects of engineering development, implementation, launch, continuous improvement, and expansion of digital product suite related to project delivery • collaborate with Engineering to develop and prioritize configuration management decision making related to features, product-market fit, and broader digital product roadmap • provides day-to-day team/technical leadership of the process • track compliance to policies and procedures and resolving or escalating any compliance issues • facilitate configuration management CM change management process and audits • engage with strategic projects to ensure configuration management can deliver the required CMIS functionality within project periods • review and approve all changes to the CMIS infrastructure where applicable • mentor the organization of CM services, concepts, policies, and procedures

About 10a Labs: 10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. Our adversarial red teaming, model evaluations, and intelligence collection enable engineering, safety, and security teams to stay ahead of evolving threats and deploy AI systems safely. About 10a Labs: 10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. Our adversarial red teaming, model evaluations, and intelligence collection enable engineering, safety, and security teams to stay ahead of evolving threats and deploy AI systems safely. About the role: As an Engineering Fellow, you will apply your technical skills to support high-impact research problems. Fellows will contribute across the project lifecycle — from processing diverse data sources and designing dynamic visualizations, to deploying sophisticated models and building cloud infrastructure. This is a hands-on role at the intersection of applied research and practical engineering, with opportunities to explore novel methods, test ideas quickly, and generate insights. Fellows specialize in one of three concentrations based on interest and past experience: Software Engineering, Data Engineering, or Machine Learning. In this role, you will: - Collaborate with engineers on real projects, including client-facing products and in-house tooling; - Assist with researching experiment design and automation, particularly as it relates to abuse detection or red teaming of AI systems; - Ideate / brainstorm new research approaches to known and novel problems in the Trust & Safety and AI Security fields; and - Support other critical initiatives. Software Engineering concentration responsibilities may include: - Implementing cloud infrastructure for deploying machine learning models; - Writing high-coverage test suites for complex codebases; and - Guiding project development with software engineering best practices, including version control, continuous integration, and design patterns. Data Engineering concentration responsibilities may include: - Sourcing, curating, and processing diverse data sources across domains and modalities, including automated collection of internet-scale datasets; - Designing data architecture schemata, implementing with production-grade data storage tools, and interfacing via custom APIs; and - Developing front-end dashboards and other visualizations. Machine Learning concentration responsibilities may include: - Training, validating, evaluating, and deploying cutting-edge machine learning algorithms including classifiers, LLMs, and computer vision models; - Building agentic systems for automated prompting, red-teaming, research, and rapid experimentation; - Supporting projects with specialized knowledge of frontier model architectures and cutting-edge technology. We’re looking for someone who: - Brings curiosity and creativity to ambiguous research problems, with a bias toward experimentation and rapid iteration; - Thrives in collaborative, interdisciplinary environments; is resourceful, proactive, and adaptable; - Is comfortable communicating technical ideas clearly to both technical and non-technical audiences; and - Is excited about contributing to real-world applications and exploring new methods that push beyond standard benchmarks. Requirements: - Strong academic background and quantitative foundation demonstrated through applied coursework, research, or hands-on-experience - Strong Python background - Clear communicator of technical concepts for non-technical audiences Nice to have: - Familiarity with Google Cloud Platform (or similar), including storage and database services (e.g., Cloud Storage, CloudSQL, Cloud Spanner), workflow orchestration (e.g., Cloud Composer/Airflow, Cloud Run, Pub/Sub), and ML services (e.g., Vertex AI, Compute Engine) - Experience managing full lifecycle projects from design to deployment Software Engineering: - - Experience designing and building end-to-end backend systems, from architecture and data modeling to deployment, scaling, and monitoring - Proficiency in backend programming languages such as Python, Java, Kotlin, Node.js, or Go and experience building secure systems, APIs, and microservices - Knowledge of security best practices, including authentication methods (OAuth, JWT), encryption, and secure API development; knowledge of common attack vectors (SQL injection, privilege escalation, DDoS) and effective mitigation strategies Data Engineering: - - Experience with web scraping/crawling (e.g., Beautiful Soup, Selenium, Scrapy) Machine Learning Engineering: - - Computer vision skills (OCR, image classification, deep fake detection) - Familiarity with multimodal learning (text-image or text-audio) or cross-domain model evaluation - Exposure to MLOps tools and practices (Docker, Kubernetes, CI/CD for ML, MLflow, etc.) - Understanding of modern retrieval-augmented generation (RAG), AI agent frameworks, and context-aware orchestration (e.g., LangChain, LlamaIndex, OpenAI Agents, or AutoGen) for building intelligent applications Benefits: - Flexible start / end dates - Remote work (based in the continental U.S.) - Flexible schedule, up to 20 hours per week (negotiable) - Hourly pay commensurate with experience and qualifications - $30 per hour for undergraduate students - $35 per hour for graduate students - $50 per hour for advanced PhD students - $60 per hour for postdocs or non-tenured positions - $125 per hour for tenure-track academics

• Design, develop, test, document, and deploy high-quality backend services into production • Build scalable, performant APIs and services that support customer-facing applications • Develop a deep understanding of our industry, products, feature set, and roadmap • Lead the technical delivery of new features from functional requirements through implementation • Contribute to architectural discussions and help define engineering standards, best practices, and guidelines • Collaborate closely with Product, Design, and other engineering teams to make technology decisions that improve our products • Participate in on-call rotations to troubleshoot and resolve production issues • Escalate risks and blockers early and proactively propose solutions • Participate in code reviews to ensure quality, consistency, and knowledge sharing • Improve system reliability, observability, testability, and operational excellence metrics • Contribute to team planning, estimation, and design discussions • Mentor junior engineers and help onboard new team members • Be open to occasional travel to Fanatics offices, conferences, and team events