Uniphore-posted 3 months ago
$205,600 - $282,700/Yr
Full-time • Senior
Palo Alto, CA
501-1,000 employees

Uniphore is one of the largest B2B AI-native companies—decades-proven, built-for-scale and designed for the enterprise. The company drives business outcomes, across multiple industry verticals, and enables the largest global deployments. Uniphore infuses AI into every part of the enterprise that impacts the customer. We deliver the only multimodal architecture centered on customers that combines Generative AI, Knowledge AI, Emotion AI, workflow automation and a co-pilot to guide you. We understand better than anyone how to capture voice, video and text and how to analyze all types of data. As AI becomes more powerful, every part of the enterprise that impacts the customer will be disrupted. We believe the future will run on the connective tissue between people, machines and data: all in the service of creating the most human processes and experiences for customers and employees.

  • Design and build distributed software systems and microservices to support large-scale conversational AI solutions, ensuring high availability, fault tolerance, and performance under heavy load.
  • Lead the development of advanced Conversational AI capabilities (NLP and generative AI models), delivering intelligent dialogue systems and virtual assistants for enterprise users.
  • Ensure end-to-end quality of AI-driven applications, including rigorous testing, test automation, performance tuning, and maintaining CI/CD pipelines for continuous integration and deployment of ML models.
  • Drive best practices in MLOps to streamline model training, validation, and rollout to production.
  • Deploy and orchestrate AI services on cloud platforms (e.g., AWS, GCP, or Azure) using containerization technologies like Kubernetes and Docker.
  • Architect solutions for real-time data processing and streaming (using technologies like Kafka or similar) to enable responsive, data-driven AI interactions.
  • Collaborate closely with research scientists, ML engineers, and product teams to integrate the latest AI breakthroughs into the platform.
  • Drive innovation by contributing to open-source projects or research publications, and foster a culture of knowledge-sharing and continuous improvement in the Conversational AI domain.
  • Bachelor’s degree in Computer Science or related field (or equivalent practical experience); advanced degree (Master’s/PhD) preferred.
  • 8+ years of software development experience, including building large-scale distributed systems or infrastructure.
  • Proven experience designing and implementing distributed systems and microservices architecture for complex applications.
  • Deep understanding of concurrency, networking, and large-scale system design.
  • Strong expertise in AI/Machine Learning, with emphasis on Natural Language Processing and Conversational AI.
  • Hands-on experience developing NLP models, dialogue management, or working with large language models (LLMs).
  • Track record of deploying and scaling AI-driven applications in production.
  • Experience with model testing/validation, performance optimization, monitoring, and managing full ML lifecycle.
  • Proficiency in modern programming languages such as Java, Go, and Python.
  • Strong coding abilities with attention to clean, maintainable code.
  • Solid knowledge of cloud platforms (AWS, Google Cloud, or Azure) and infrastructure-as-code.
  • Experience with containerization and orchestration (Docker, Kubernetes).
  • Familiarity with continuous integration/continuous deployment tools and workflows.
  • Familiarity with real-time data processing and streaming architectures (e.g., Kafka, Apache Flink).
  • Working knowledge of databases, including both SQL and NoSQL data stores.
  • Excellent communication and teamwork skills.
  • Experience working in cross-functional and matrixed teams.
  • Demonstrated leadership in mentoring engineers and driving technical vision.
  • Contributions to open-source projects or authorship of technical publications in AI/ML.
  • Competitive base pay.
  • Annual incentive opportunity based on target achievement.
  • Pre-IPO stock options.
  • Medical, dental, vision insurance.
  • 401(k) with a match.
  • Generous paid time off.
  • Paid holidays.
  • Paid day off for your birthday.
  • Other paid leave policies to support employees through all phases of life.
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