Jobs at Cerence Inc.

Lead development of the application and cognitive layer for humanoid robots: implement behavior trees and intent-to-action orchestration, build voice applications and multi-modal fusion, integrate robotics capabilities and edge/cloud AI services, and ensure production readiness with CI/CD, telemetry, and monitoring.

Own full sales and partnership cycle to bring voice AI to mobile service robots: engage senior robotics decision-makers, qualify and prioritize opportunities, close deals, and shape the commercial playbook while operating autonomously within a small technical team.

Own end-to-end software architecture for humanoid robot applications, design modular, production-ready platforms integrating robotics frameworks, AI, cloud/edge, and hardware constraints; lead technical decisions, guide POCs to deployments, and mentor a small engineering team.

Lead technical engagements with robotics customers to design and integrate voice AI into mobile robots, own POCs and technical evaluations, clear deployment roadblocks, collaborate with sales/product/services, and feed customer learnings into the product. Travel across Europe for onsite evaluations (20–30%).

Lead enterprise sales for automotive dealer groups, owning the full sales cycle from pipeline development through close. Build relationships with dealer principals and operational leaders, conduct high-value discovery, lead pricing and contract negotiations, support demos and pilots, and convert pilots to paid customers. The role focuses on multi-rooftop deals, pipeline quality, revenue per deal, conversion rates, and representing Cerence at industry events. Approximately 30% travel to customer sites is required.

Lead design and training of large-scale transformer and hybrid foundation models across text and multimodal domains. Own architecture choices, diagnose large-scale training instabilities, optimize scaling tradeoffs (data, compute, model), design loss and alignment strategies, and execute distributed training (FSDP/ZeRO, tensor/pipeline parallelism) with mixed precision to build in-house foundation model expertise.

Lead development and optimization of high-performance LLM inference pipelines across data center, edge, and embedded platforms. Improve latency and throughput via custom CUDA kernels, quantization, KV-cache and batching strategies, and deploy efficient, production-ready runtimes without external vendor dependency.

Customer-facing sales role responsible for owning direct opportunities and managing channel/distributor relationships to drive revenue. Duties include discovery, proposals, demos, negotiation, pipeline management, partner enablement, co-selling, event representation, and cross-functional coordination to support go-to-market and product launches. Targets include bookings, distributor-sourced pipeline growth, and executing partner workshops.

Design and implement advanced generative AI models, optimize deployment in production, collaborate with teams, and stay updated on AI advancements.

Design, build, and operate distributed GPU training infrastructure for large neural networks. Optimize multi-node/multi-GPU execution, diagnose compute/memory/network bottlenecks, improve stability and fault tolerance, and partner with research teams to productionize large-model training pipelines for reliable, high-throughput training at scale.

Design and implement advanced Generative AI models, optimize performance for LLMs, and collaborate with cross-functional teams to innovate AI solutions within the automotive sector.

Design, build, and maintain FinOps tooling, data pipelines, dashboards, and automation to improve cloud cost visibility, allocation, and optimization across Azure, AWS, and GCP. Support budgeting, variance analysis, anomaly detection, and executive reporting. Collaborate cross-functionally to implement tagging, chargeback/showback, governance, and AI-enabled automation while documenting operational processes for scalable FinOps practices.