This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Ford’s Electric Vehicles, Digital and Design (EVDD) team is charged with delivering the company’s vision of a fully electric transportation future. EVDD is customer-obsessed, entrepreneurial, and data-driven and is dedicated to delivering industry-leading customer experience for electric vehicle buyers and owners. You’ll join an agile team of doers pioneering our EV future by working collaboratively, staying focused on only what matters, and delivering excellence day in and day out. Join us to make positive change by helping build a better world where every person is free to move and pursue their dreams. - Drive architecture and technical strategy for high-reliability software systems within your organization. - Apply expertise in verification automation to improve reliability and controls on software deployed into complex systems related to their functionality, safety, and security. - Champion reliability, performance, and other quality initiatives across domains based on data-driven insights. - Advance the state of the art for high-quality software development by improving standard practices to optimize for development speed without sacrificing correctness. - Design and implement tools & infrastructure for formal verification, symbolic reasoning, and constraint solving. - Integrate automated reasoning into existing software development life cycle systems (e.g. CI). - Collaborate across functional team boundaries to deliver integrated solutions. Qualifications - 10+ years of Rust-lang development experience. - Working expertise in additional languages such as Python and Typescript. - 15+ years of experience as a software engineer, preferring a backend focus. - Mastery of advanced automated testing & software quality methods such as property-based testing, fuzzing, and model checking. - Strong background in formal logic, automated theorem proving, and tools & technologies such as Z3, TLA+, and Alloy. - Experience mentoring and advancing the skills of engineering teams. Requirements - At least 7 years of technical leadership doing architecture, mentorship, and advance individual contribution. - Production experience with automated reasoning capabilities and pipelines at scale. - Significant DevOps / SRE experience supporting business-critical services live for internal and external customers. - Experience with operational incident management and risk mitigation. Benefits - Immediate medical, dental, vision and prescription drug coverage. - Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more. - Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more. - Vehicle discount program for employees and family members and management leases. - Tuition assistance. - Established and active employee resource groups. - Paid time off for individual and team community service. - A generous schedule of paid holidays, including the week between Christmas and New Year’s Day. - Paid time off and the option to purchase additional vacation time.

• Design, build, and optimize machine learning models to enhance Xometry’s platform and business operations. • Analyze large datasets to extract meaningful patterns and insights. • Collaborate with cross-functional teams to integrate machine learning models into production systems. • Learn and apply best practices in model evaluation, performance tuning, and deployment. • Influence technical direction by identifying opportunities to improve modeling approaches, data quality, and system architecture. • Work across teams to ensure machine learning solutions are explainable, maintainable, and aligned with business goals. • Help bridge the gap between research and production, ensuring models perform just as well in the real world as they do in notebooks. • Gain exposure to cutting-edge machine learning frameworks, tools, and techniques used in the manufacturing industry.

• Develop MLOps frameworks and workflows for a variety of domains and applications • Deploy, maintain, and optimize ML models and data processes in a production environment • Develop custom AI/ML algorithms that translate into mission value • Conduct experiments, evaluate model performance, and fine-tune algorithms to improve accuracy and efficiency • Collaborate with cross-functional teams to integrate AI/ML models into products and services

• Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases. • Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact. • Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases. • Leverage third-party and in-house Machine Learning tools & infrastructure to develop reusable, highly differentiating and high-performing Machine Learning systems, enable fast model development, low-latency serving and ease of model quality upkeep. • Example projects include: feature platform, model interpretability, hyperparameter optimization, concept drift detection.