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Sr. AI Engineer
Sr. AI EngineerMursion Inc • San Francisco, CA, United States
Sr. AI Engineer

Sr. AI Engineer

Mursion Inc • San Francisco, CA, United States
1 day ago
Job type
  • Full-time
Job description

About Mursion

Mursion provides an award-winning upskilling platform trusted by top companies to measurably improve employees' interpersonal intelligence and build stronger organizations. Powered by multimodal AI and a unique practice-based approach, our real-world, interactive simulations deliver lasting results. Our solutions are grounded in behavioral science and psychology to build confidence and positive behaviors, and ultimately help reduce the costs of stress. Mursion’s product suite includes AI-powered simulations, human reinforcement assessment & coaching, and advanced analytics that lead to measurable skills acquisition.

Mursion is a well-funded Series B startup that is backed by future of work and Edtech investing veterans, like Leeds Illuminate and New Markets Venture Partners. Mursion is the largest simulation company, with more than 800K+ simulations to date and more than 200K users per year, with a growing global footprint. By 2026, we will be delivering 2 million simulations per year.

Who We Want : We seek talented people from diverse backgrounds and experiences, who are inspired by our mission to leverage virtual reality technology to reinvent professional learning, and who are motivated to help Mursion become the premier global platform for virtual simulation training for behavioral skills. We value empathy, curiosity, and constant improvement both in our internal operations and when working with partners and clients. Our employees are most successful when they employ strong collaboration skills, skilled communications, a problem-solving orientation, and demonstrate comfort in an evolving and fast-paced startup environment.

About the role

As a Senior AI Engineer for Real-Time Conversational Agents, you will play a crucial role in developing and deploying the real-time AI systems that power our conversational agents. You’ll work primarily with large language models (LLMs), automatic speech recognition (ASR), text-to-speech (TTS), and emerging speech-to-speech models, and you’ll use modern agent and real-time frameworks to ship low-latency, production-ready experiences.

We care deeply about model stability, latency, evaluation, and observability, and we’re constantly iterating to adopt new foundations and improve our routing and model-hopping strategies.

Responsibilities

  • Develop and maintain real-time speech-to-speech conversational agents, collaborating closely with product, design, and research teams.
  • Ship low-latency, high-impact features that directly enhance user experience, with clear performance and product metrics.
  • Design and optimize STS pipelines that integrate DeepGram, LiveKit / WebRTC, ElevenLabs, OpenAI, VAD, and Lambda-style architectures.

Drive core improvements to our AI infrastructure, including :

  • Latency and stability optimizations across ASR → LLM / agent → TTS / speech-to-speech pipelines.
  • Robust error handling, fallbacks, and model hopping strategies across providers and models.
  • Instrumentation, evaluation, and monitoring for quality, drift, and robustness.
  • Execute major projects from concept to production, owning design, implementation, rollout, and iteration based on real-world feedback.
  • Collaborate with data scientists, software engineers, and product managers to translate requirements into measurable AI features tied to business outcomes.
  • Preprocess and analyze large multimodal datasets (audio, transcripts, interaction logs) to extract features and insights for model evaluation and improvement.
  • Implement and optimize algorithms for performance, scalability, efficiency, and cost, particularly in real-time streaming environments.
  • Monitor and maintain models and systems in production, with attention to :

  • Latency budgets and tail performance
  • Stability, load, and failure modes
  • Continuous evaluation and A / B testing
  • Stay up-to-date with the latest in generative AI, speech, and real-time systems (e.g., new speech-to-speech models, WebRTC and streaming advances) and drive integration where it makes sense.
  • Contribute to model fine-tuning and adaptation work (e.g., custom LLM / alignment, TTS / ASR domain adaptation) where it materially improves product quality, while prioritizing real-time reliability and UX.
  • Participate in code reviews, testing, and debugging to ensure high-quality, maintainable deliverables.
  • Qualifications

  • 4+ years of experience as a Machine Learning Engineer, AI Engineer, or related role.
  • Proven experience developing and deploying ML / AI capabilities into production and serving real users.
  • Strong programming skills in Python. You should be an expert in Python.
  • Solid understanding of core MLOps and software architecture for modern ML-based applications (CI / CD, monitoring, rollback strategies, feature flags, etc.).
  • Strong grasp of data structures, algorithms, and statistical methods.
  • Experience with real-time or streaming systems (e.g., WebRTC, LiveKit, low-latency APIs, event-driven / Lambda architectures) or a strong desire to work in this space.
  • Excellent problem-solving skills and the ability to work both independently and collaboratively.
  • Strong communication skills for working with cross-functional teams.
  • Strong candidates will have

  • Bachelor’s or Master’s degree in Computer Science, or a related field.
  • A lot of enthusiasm for applying AI to real business problems and product use cases.
  • Experience with ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, etc.
  • Experience with LLMS, NLP, speech technologies (ASR / TTS / VAD), conversational agents, and / or reinforcement learning.
  • Familiarity with model fine-tuning, evaluation frameworks, and A / B testing for model and routing changes.
  • Experience with DevOps practices and tools for CI / CD.
  • Experience with cloud platforms (AWS, Google Cloud, Azure) and containerization (Docker, Kubernetes).
  • Exposure to model routing / model hopping across providers and versions to balance cost, quality, and latency.
  • Competitive Salary, bonus eligibility and equity
  • 401K, Flexible PTO
  • Health Care Plan (Medical, Dental & Vision)
  • Retirement Plan (401k)
  • Life Insurance (Basic, Voluntary & AD&D)
  • Parental Leave
  • Short Term & Long Term Disability
  • Work From Home
  • #J-18808-Ljbffr

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