AI Infrastructure Engineer; Remote

Company: Speechify
Location: Remote (Global)
Also See: Lead AI/Dev Ops Engineer

Speechify is on a mission to eliminate reading as a barrier to learning. Our award‑winning text‑to‑speech platform is used by over 50 million people to convert any text into natural audio, empowering users to read faster, learn more, and improve accessibility. Recognized by Google and Apple, we are a fully remote, 200‑person team of elite engineers and researchers from top tech companies, building the future of AI‑powered audio.

You will be the key builder of our ML ecosystem, partnering closely with Data Science and Product teams to transform experimental models into reliable, high‑performance production systems used by millions daily.

• Architect & Scale AI Infrastructure:
  Design, build, and maintain high‑performance, scalable platforms for model training and real‑time inference.
• Develop MLOps Tooling:
  Create self‑service tools and pipelines that enable ML engineers to deploy models in minutes, dramatically accelerating the research‑to‑production lifecycle.
• Optimize Performance & Cost:
  Ensure our training and serving systems are highly reliable, cost‑efficient, and optimized for performance, including GPU utilization and low‑latency streaming.
• Automate & Standardize:
  Establish and automate best practices for model versioning, testing, monitoring, and governance across the entire ML workflow.
• Collaborate Cross‑Functionally:
  Partner with AI researchers and data scientists to product ionize breakthrough voice models and build robust data/model pipelines.

• 3+ years of experience in Software Engineering, ML Platform, or Infrastructure roles, with a focus on cloud‑native distributed systems and MLOps.
• Technical Expertise:
  Proficient in Python, Kubernetes, Docker, and major cloud platforms (AWS/GCP/Azure). Strong experience with infrastructure‑as‑code (Terraform) and CI/CD.
• MLOps Proficiency:
  Hands‑on experience with ML frameworks (PyTorch/Tensor Flow) and orchestration tools (Kubeflow, MLflow, Airflow).
• Systems Thinker:
  Deep understanding of data pipelines, model deployment strategies, real‑time inference, and building reliable, observable AI systems.
• Excellent Communicator:
  Ability to collaborate effectively across engineering and data science teams in a fully remote, asynchronous environment.
• Bonus/Nice‑to‑Have:
  
  Experience with GPU optimization (Tensor
  
  RT, vLLM), vector databases, feature stores, streaming technologies (Kafka), or audio/streaming systems.

• Massive Impact:
  Build infrastructure for a product that directly improves the lives of millions, especially those with dyslexia, ADHD, and other learning differences.
• Elite Remote Team:
  Work with top‑tier talent from Google, Microsoft, Stripe, and leading PhD programs in a 100% distributed, autonomous culture.
• Cutting‑Edge Domain:
  Operate at the forefront of AI and audio technology—one of the most dynamic and revolutionary fields in tech.
• Ownership & Innovation:
  Enjoy significant autonomy to shape our core AI platform in a dynamic, high‑growth environment.
• Competitive Compensation & Culture:
  Receive competitive pay and contribute to an exceptional, inclusive, and asynchronous work culture.

If you are a systems‑builder passionate about creating the platform that will power the next generation of AI voice models, we want to hear from you.

(Use the "Apply for this Job" box below)./

Speechify is an equal opportunity employer committed to diversity and inclusion.

Tagged as: AI Infrastructure Engineer, AI Platform, Cloud AI, Kubernetes, Machine Learning Platform Engineer, ML Infrastructure, MLOps Engineer, PyTorch, Tensor Flow