• Planning and design of medium- and low-voltage networks (distribution and connection networks) • Network calculations and simulations (load flow, short-circuit, voltage drop) • Integration and assessment of renewable energy installations under the EEG (e.g., PV, wind, storage) • Planning and sizing of substations and transformer stations • Supporting our clients in preparing grid connection applications • Preparation of planning documents, concepts, and documentation • Coordination with grid operators, clients, and project stakeholders • Contributing to innovative solutions in the field of power networks (e.g., smart grids, network optimization)

Title: Forward Deployed Engineer Location: San Francisco Department: Commercial Job Description: Unstructured is defining the standard for enterprise data transformation in the age of LLMs and generative AI. In just two years, we've raised over $65M from world-class investors, including Menlo Ventures, Bain Capital, Databricks, NVIDIA, Microsoft, and IBM. Our open-source toolkit has been downloaded 61M+ times and is used by 90% of the Fortune 1000. We power production AI workflows across commercial and federal sectors — transforming PDFs, HTML, Word docs, images, emails, and more into AI-ready data pipelines that scale. We're not just building tools, we're building the backbone of generative AI and the infrastructure that unlocks intelligence across industries. The Mission Ready to drive real-world impact by helping enterprises harness the power of unstructured data and AI? At Unstructured, we’re building the backbone of generative AI—enabling companies to transform PDFs, HTML, Word docs, images, and more into enterprise-grade data pipelines. Our open-source package has been downloaded over 52+ million times, with adoption across 50,000+ companies, including nearly half of the Fortune 500. We’re entering our next chapter of growth, and we’re hiring an experienced Forward Deployed Engineer to help bring our commercial customers from purchase to production with ease. If you're a technical problem solver who loves working directly with customers, designing real-world solutions, and seeing impact fast - this is your moment. You’ll be a core part of our commercial team, leading enterprise deployments, building scalable cloud-native architectures, and ensuring customers unlock the full potential of our platform. What You’ll Own & Drive Lead High-Impact Deployments Design and deliver secure, scalable post-sales implementations for commercial customers—across AWS, GCP, and Azure Be the Trusted Technical Partner Guide customers through architecture, integration, optimization, and tuning—especially around AI/LLM and RAG use cases Build the Toolkits That Scale Create reference architectures, onboarding guides, and playbooks that reduce time-to-value and accelerate adoption Drive Technical Success Run enablement sessions, whiteboarding workshops, and POCs to maximize customer value and foster long-term partnerships Troubleshoot the Hard Stuff Solve complex infrastructure and data pipeline issues—ensuring stability, observability, and high performance Shape the Product Feed customer insights directly to Product & Engineering to shape our roadmap and improve enterprise capabilities What You Bring - 5+ years of experience in post-sales engineering, solutions architecture, or technical consulting - Deep experience with cloud-native architectures (AWS, Azure, GCP), containers (Docker, Kubernetes), and IaC tools - Strong hands-on Python skills for scripting, API integration, and automation - Proven success leading enterprise-scale deployments and solving real customer problems with technical precision - Excellent communicator—you simplify the complex and build trust across both engineering and business audiences - Comfort navigating ambiguity and speed—especially in startup or high-growth environments - Willing to travel up to 20% Bonus Points - Experience delivering or optimizing RAG pipelines, vector databases, or LLM-based applications - Knowledge of DevSecOps best practices and commercial security/compliance frameworks (SOC 2, ISO 27001) - Familiarity with both pre-sales and post-sales solutioning across AI/ML workflows - Startup DNA - you move fast, stay scrappy, and take ownership end-to-end Why You’ll Love It Here - Real Customer Impact: Work with top global companies solving bleeding-edge AI use cases - Mission-Critical Work: Your solutions will directly power AI deployments in production - Ownership & Autonomy: Be trusted to drive results and innovate from day one - Elite Team: Join world-class builders who value humility, speed, and precision - Strong Benefits: Competitive salary, full health benefits, equity, and parental leave You'll be surrounded by smart, kind, low-ego people who genuinely enjoy building together. We invest in our team with company offsites, best-in-tech swag, and the tools you need to do your best work, wherever you're based. We support you holistically, not just at work. From medical, dental, and vision coverage effective the 1st of the month following your start date, life and disability insurance, unlimited PTO, and flexible parental leave, to a 401(k) with company match, equity, a $500 work from home stipend, $70/month internet reimbursement, and team/company offsites throughout the year - we want you focused on building, growing, and staying energized for the long haul. Ready to help companies unlock the full power of unstructured data? Apply now to join Unstructured and shape the future of AI delivery.

• Act as the technical cornerstone between security policies and operational implementation. • Ensure that complex business logic and access frameworks translate accurately into robust configurations. • Unpack existing technical guidelines and configure seamless directory synchronization, authentication, and access management across enterprise environments.

Role Description Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Manufacturing - Automotive (Mechanical Engineering) Expert Type: Contract Compensation: $45–$65/hour Location: Remote Role Responsibilities - Build a realistic digital workspace centered on the Drive folders you use daily. - Include design reviews, DFMEA / PFMEA documents, PPAP packages, tolerance analyses, benchmarking decks, test reports, and email threads. - Represent platforms like ANSYS Fluent / STAR-CCM+, Siemens Opcenter, SAP S/4HANA. - Design multi-step tasks grounded in real workflows. - Navigate multiple apps, files, and stakeholders to challenge frontier AI agents. - Collaborate with other automotive engineering experts to design the environment. - Shape task scope and review scenarios for realism and rigor. - Work asynchronously with research teams to refine task designs and evaluation criteria for automotive engineering agent benchmarks. - Contribute to frontier AI research and benchmarking. - Your work directly informs how leading labs train and evaluate the next generation of AI systems. Qualifications - Must-Have: BS/MS in Mechanical Engineering or related discipline. - 3+ years of full-time experience at a Fortune 500 automotive OEM or Tier-1 supplier. - Background in vehicle or subsystem design, CAE / CAD / simulation engineering, manufacturing/process engineering, or quality engineering. - Day-to-day use of ANSYS Fluent / STAR-CCM+, Siemens Opcenter or Rockwell FactoryTalk, and SAP S/4HANA. - Strong analytical thinking and writing skills. Requirements - This project will transition from an effective hourly rate to compensation based on throughput of quality work. Application Process - Upload resume - AI interview based on your resume - Submit form Resources & Support - For details about the interview process and platform information, please check: Interview Process - For any help or support, reach out to: support@mercor.com - Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.