Role Description As a Staff / Senior Staff CAD & Methodology Engineer, you will be the resident expert in Innovus and Tempus, responsible for developing, debugging, and continually accelerating our RTL-to-GDSII and timing signoff flows. You will work closely with Physical Design and STA leads to eliminate bottlenecks, automate manual tasks, and push the limits of EDA capabilities at advanced process nodes. Key Responsibilities - Flow Architecture & Automation: Architect, develop, and maintain a highly automated, robust, and scalable physical design and signoff flow from synthesis through GDSII, optimized for AI accelerator architectures. - Innovus Methodology: Drive advanced physical design methodologies in Cadence Innovus. Optimize recipes for floorplanning, placement, Clock Tree Synthesis (CTS), routing, and power grid implementation to squeeze out maximum PPA. - Tempus Signoff Integration: Own the STA and timing signoff methodology using Cadence Tempus. Implement and optimize Distributed Multi-Scenario Analysis (DMSA), advanced OCV methodologies, and automated Tempus ECO flows to ensure rapid timing closure. - Turnaround Time (TAT) Reduction: Identify inefficiencies in the daily execution of block and top-level implementation. Develop Python and Tcl-based automation, database parsers, and custom utilities to drastically reduce tool runtime and engineering debug time. - Tool & Vendor Interface: Act as the primary technical liaison with Cadence. Drive tool evaluations, beta testing of new features, and resolution of critical tool bugs or limitations to ensure continuous flow stability. - Mentorship & Support: Serve as the final escalation point for the PD and Timing teams regarding flow-related issues. Document methodologies clearly and mentor junior engineers on tool usage and flow mechanics. Qualifications - Experience: 9 to 14 years of industry experience in ASIC/SOC physical design, with a primary focus on CAD, TFM (Tools, Flows, and Methodology), or flow automation. - Cadence Mastery: Deep, production-proven expertise with Cadence Innovus (Implementation) and Cadence Tempus (Signoff STA). Strong understanding of internal tool mechanics, database access commands (dbGet), and advanced tool configuration. - Scripting & Software Skills: Expert-level proficiency in Tcl and Python. Strong background in Makefile generation, shell scripting, and version control (Git/Perforce). - Domain Knowledge: Thorough understanding of deep sub-micron physical design concepts (advanced node DRCs, cross-talk, electromigration, IR drop) and the theoretical foundations of Static Timing Analysis. - Startup Mindset: Ability to thrive in a fast-paced, dynamic environment where flow requirements evolve rapidly as the architecture matures. - Education: Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, Computer Engineering, or a related discipline.

• Serve as a senior technical advisor for electrical substation, underground transmission, protection, and control projects • Provide senior-level technical leadership and engineering expertise for substation and transmission projects • Independently plan, execute, and oversee complex engineering assignments • Evaluate, adapt, and develop engineering solutions to address technical challenges • Mentor and supervise junior engineers and technical staff • Ensure compliance with applicable design codes, building codes, OSHA, FERC, NERC, and CIP standards • Support cost-benefit analyses and evaluation of alternative engineering approaches • Develop technical specifications for services, equipment, and materials • Coordinate with clients, consultants, contractors, vendors, and internal project teams • Review and provide comments on engineering drawings, calculations, specifications, and design deliverables • Assist with bid evaluations, contract reviews, and award recommendations • Prepare technical reports and engineering documentation for executive and public review • Provide expert technical testimony and support when required • Communicate effectively with stakeholders at all levels, both verbally and in writing • Analyze and resolve complex technical issues using sound engineering judgment

• Monitor production network environment using a combination of monitoring tools to ensure availability. • Work with Business customers, Residential customers and techs in the field installing new services via phone. • Troubleshoot issues remotely with customers and technicians in the field • Coordinate onsite dispatch of Telecommunication vendor repair services. • Respond to automated alerts from monitoring tools according to procedure. • Use diagnostic tools to ascertain level and criticality of problem. • Discover faults and conditions in a proactive manner. • Diagnose cause where appropriate and resolve expeditiously. • Escalate issues and problems according to procedures and best judgment. • Perform periodic health checks of systems. • Use judgment and knowledge of networking, systems, and SMS applications to identify problems as they occur and decide on best course of action to resolve. • Diagnose problems and resolve in an expeditious manner. • Work with Engineers to resolve production problems. • Responsible for configuring and maintaining monitoring tools. • Answering direct phone calls from customers

Role Description Turn audience science into scalable production systems that help advertisers decide whom to reach. Working with terabyte-scale data, you'll build, score, refresh, and deliver audience segments to activation endpoints across DSPs, clean rooms, CTV, social, and programmatic partners. You bridge data science and platform engineering—converting prototypes into production-grade services and owning the pipelines, MLOps, and integrations behind them. As a senior team member, you'll set engineering standards, lead end-to-end system design, and mentor other engineers. Stack: Databricks, Spark, Snowflake, and Azure. Responsibilities - Convert data science prototypes (propensity, lookalike, segmentation, fusion) into reproducible, production-quality ML services. - Build and operate large-scale data/feature pipelines on Databricks + Spark, reading from and writing to Snowflake, producing versioned audience segments on schedule. - Own the full model lifecycle: MLflow tracking/registry, CI/CD (Azure DevOps or GitHub Actions), automated retraining, drift monitoring, and rollback. - Engineer the activation layer, governed delivery of segments and scores into DSPs/SSPs, DMP/CDP, clean rooms, and CTV/social/programmatic partners, including identity resolution and onboarding. - Ensure scalability, latency, cost-efficiency, and reproducibility across Azure (ADLS, Azure ML, AKS); support batch and near-real-time scoring. - Enforce privacy-by-design: data minimization, access controls, encryption, and clean-room-compatible patterns. Qualifications - 8–9 years hands-on ML engineering, shipping and operating production systems at scale. - Prior experience in media / advertising / audience activation. - Databricks (incl. MLflow and Spark), Snowflake, and production Azure (ADLS, Azure ML, Azure DevOps, AKS). - Expert Python and ML ecosystem; strong SQL at scale. - Strong applied statistics (sampling/weighting, forecasting, causal inference, or experimental design). - CS/engineering degree with strong quantitative foundations. Requirements - Agile practices, Docker/Kubernetes, advanced Databricks/Snowflake (Structured Streaming, tuning, Model Serving/Feature Store), orchestration (Databricks Workflows, Airflow, Dagster). - Ad tech/identity experience: DSP/SSP, DMP/CDP, clean rooms (LiveRamp, Snowflake), identity graphs, onboarding, delivery APIs. - AWS/GCP a plus. About you - Pragmatic and deeply hands-on about production trade-offs; a clear communicator with non-expert stakeholders; a proactive team player who mentors others. - Comfortable working the second half of the day to overlap with a US-based product team. - Fluent in an English-language business environment. Company Description Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic) and more than 450 full-time employees, Fusemachines brings global AI expertise to transform companies worldwide. Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government.