Member of Technical Staff, Multimedia Jobs

Fireworks AI

Location:
United States, San Mateo

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

We are looking for highly motivated engineers and researchers to join our Multimedia team as Members of Technical Staff. In this role, you will help advance Fireworks AI’s capabilities across speech, vision, and multimodal systems, from deploying and training models to building the infrastructure that powers real-time, production-ready AI experiences. We welcome both generalists with broad multimedia expertise and specialists with deeper focus in speech/audio or vision-language modeling. You will work at the intersection of research and engineering, turning cutting-edge model innovation into high-performance, scalable systems that power Fireworks AI’s next-generation products.

Job Responsibility:

Design, train, and implement machine learning models for speech, vision, or multimodal applications, including ASR, TTS, image understanding, captioning, retrieval, and speech-to-speech systems
Bring new model capabilities from research to production, ensuring high performance and reliability
Build and optimize the infrastructure that supports distributed training, fine-tuning, and real-time inference across multimedia workloads
Profile and address performance bottlenecks across the stack, from preprocessing and model training to deployment and serving
Write high-quality, maintainable code for both experimentation and production systems
Evaluate and integrate the latest research to improve model performance, scalability, and efficiency
Work directly with internal and external stakeholders to define use cases, deliver custom optimizations, and inform the multimedia roadmap
Contribute to open-source efforts and help shape the future of multimodal AI at Fireworks

Requirements:

Bachelor’s degree in Computer Science, Electrical Engineering, or a related technical field
3–5+ years of experience in machine learning, backend infrastructure, or data-intensive systems
Strong proficiency in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow
Demonstrated experience in one or more of the following areas: Speech or audio modeling (ASR, TTS, speech-to-speech)
Vision or vision-language modeling (captioning, VQA, retrieval, multimodal reasoning)
Backend or infrastructure engineering for ML workloads (training, inference, optimization, APIs)
Experience building production-quality systems and collaborating across research and engineering teams
Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization/orchestration tools (Docker, Kubernetes)

Nice to have:

Master’s or PhD in a relevant technical field with research experience in speech, vision, or multimodal modeling
Experience deploying and optimizing ML models in production, including distributed training, fine-tuning, or inference optimization
Familiarity with model optimization techniques such as quantization, speculative decoding, or parameter-efficient fine-tuning (LoRA or QLoRA)
Background in multimodal AI infrastructure or experience at a hyperscaler, AI infrastructure startup, or LLM platform
Strong understanding of GPU performance, networking, and scaling for multimedia workloads
Contributions to open-source projects or published first-author research papers in top-tier conferences such as NeurIPS, ICML, CVPR, ACL, or Interspeech
Ability to thrive in a fast-paced, low-process environment and drive high-impact, company-defining work

What we offer:

Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation

Additional Information:

Job Posted:
December 08, 2025

Employment Type:

Fulltime

Work Type:

On-site work

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Member of Technical Staff, Multimedia