This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are seeking a Machine Learning Engineer to build out our simulation and AI capabilities. You'll design and implement systems that model the CTV advertising ecosystem — auction dynamics, bidding strategies, campaign outcomes, and counterfactual scenarios — and develop AI-driven tools that accelerate how we build, test, and deploy ML systems. - Design and build simulation environments that model CTV auction mechanics, inventory supply, and advertiser competition - Develop counterfactual and what-if frameworks for evaluating bidding strategies, budget allocation, and pacing algorithms offline - Build AI agents that explore strategy spaces, generate hypotheses, and automate experimentation within simulated environments - Use LLMs and generative AI to accelerate internal ML workflows — synthetic data generation, code generation, automated analysis, and rapid prototyping - Use simulation to de-risk ML model deployments — validate new bidding and optimization strategies before they touch live traffic - Define the technical direction for simulation and AI infrastructure and mentor engineers on the team Qualifications - Strong production Python skills and experience building simulation or modeling systems - Deep understanding of probabilistic modeling, stochastic processes, or agent-based simulation - Hands-on experience with modern AI tools: LLMs, code generation, agentic workflows — and good judgment about when they help vs. when they don't - Adtech experience: you understand auction theory, RTB mechanics, and the dynamics of programmatic advertising - Ability to translate business questions ("what happens if we change our bid strategy?") into rigorous simulation frameworks - Clear written communication: you'll be defining new technical directions and need to bring others along - Ownership: you scope, design, and ship systems end-to-end with minimal direction Requirements - Causal inference — uplift modeling, synthetic controls, difference-in-differences, or incrementality testing - Experience with discrete event simulation, Monte Carlo methods, or digital twins - Reinforcement learning — using simulated environments for policy learning and evaluation - Experience building agentic AI systems or multi-agent simulations - Big data experience with Scala and Spark - Systems programming experience in Zig or similar (C, C++, Rust) - MLOps experience — model deployment, monitoring, and pipeline orchestration on AWS In-Office Requirement Statement We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role. Relocation Statement This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model. Salary Information At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise. US based applicants only $123,696 — $254,667 USD

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description tvScientific is looking for a Senior MLOps Engineer! You'll be working with a distributed engineering team on our Connected TV ad-buying platform, as we scale our Machine Learning practice. We’ve cracked the code on optimizing TV ad campaigns. We’re scaling massively and we need your help to make that scale sustainable. - Scale the decision-making process for tools for the tvScientific AI team, from our workflows to our training infrastructure to our Kubernetes deployments - Improve the developer experience for the data science team - Upgrade our observability tooling - Serve as a technical lead and mentor to the team - Make every deployment smooth as our infrastructure evolves Qualifications - Deep understanding of Linux - Excellent writing skills - A systems-oriented mindset - Experience in high-performance software (RTB, HFT, etc.) - Software engineering experience + reliability (e.g. CI/CD) expertise - Strong observability instincts Requirements - Reverse-engineering experience - Terraform, EKS, or MLOps experience - Python, Scala, or Zig experience - NixOS experience - Adtech or CTV experience - Experience deploying a distributed system across multiple clouds - Experience in hard real-time low-latency (<10 ms) environments In-Office Requirement Statement We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role. Relocation Statement This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model. Salary Information At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise. US based applicants only $155,584 — $320,320 USD

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.