Top Tech Jobs & Startup Jobs

Develop and release production-ready software by translating research prototypes into scalable solutions. Responsibilities include collaborating with R&D, automated stability and performance testing, agentic programming, CI/CD pipeline development, Git conflict resolution, code optimization, release documentation, and maintaining technical architecture documentation. The role also requires applying C/C++, Java, Python, deep learning, LLM, and ONNX knowledge to automotive AI voice technology.

Develop and maintain Python-based speech output tools, DevOps workflows, and CI/CD pipelines using Jenkins and GitLab. Analyze pipeline failures, improve tool performance, and support Docker and Kubernetes environments. Contribute to AI and MLOps initiatives involving speech and language model deployment, monitoring, and new product prototypes. The role also offers opportunities to work with Azure AI services, cloud-hosted machine learning, and generative AI tools.

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.

Integrate and deliver voice recognition software for automotive, collaborating with clients and internal teams, while setting up CI/CD environments and handling testing.

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.

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.

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%).