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Symbl.ai

Machine Learning Engineer - Infrastructure and Operations

Sorry, this job was removed at 03:12 a.m. (CST) on Thursday, Apr 09, 2026
Easy Apply
Remote
Hiring Remotely in United States
Easy Apply
Remote
Hiring Remotely in United States

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Elevating the quality of human life through every conversation

Machine Learning Engineer - Infrastructure and Operations
Location: United States (we are fully remote)
Experience: 5 years to 10+ years


About the Team :

We are seeking a skilled ML Engineer - Infra and Ops to join our team. In this role, you will play a pivotal part in our cutting-edge projects that drive AI innovation. If you are passionate about shaping the future of AI and machine learning infrastructure, we encourage you to apply and be a part of our journey.


About the Role:

As a Machine Learning Engineer specializing in Infrastructure and Operations, you will play a crucial role in optimizing and scaling our AI systems for maximum performance and reliability. We leverage a range of technologies, including but not limited to:

  • Machine Learning Frameworks
  • Cloud Computing Services
  • DevOps Tools
  • Containerization Technologies
  • Distributed Systems
  • Monitoring and Logging Solutions
  • CI/CD Pipelines

Highlights for ML Engineer - Infra and Ops:

As a Machine Learning Infrastructure or Ops Engineer at Symbl.ai, you will architect and maintain a robust, scalable infrastructure, deploying and optimizing machine learning models while ensuring data security and compliance. Join us to drive AI innovation.
Working as a ML Engineer - Infra and Ops, you will:

  • Architect and maintain robust and scalable machine learning infrastructure.
  • Collaborate with data scientists and engineers to deploy and monitor machine learning models.
  • Implement automated workflows for model training, validation, and deployment.
  • Optimize and fine-tune the performance of machine learning systems.
  • Ensure data security, privacy, and compliance within the machine learning infrastructure.
  • Troubleshoot and resolve infrastructure-related issues.
  • Contribute to the evaluation and adoption of new technologies and tools in the machine learning space.

To excel in this role, you should:

  • Possess a strong background in machine learning, computer science, or a related field.
  • Have 5+ years of experience in building and deploying machine learning models in production environments.
  • Demonstrate proficiency in cloud computing platforms such as AWS, GCP, or Azure.
  • Have experience with containerization technologies like Docker and orchestration tools like Kubernetes.
  • Exhibit strong problem-solving skills and the ability to troubleshoot complex technical issues.
  • Possess excellent communication and collaboration skills to work effectively in a remote team environment.

Please Note: Although we have focused centers in Seattle, WA there are no restrictions on where you can be located for this role - Symbl is fully remote.

Benefits and Perks (US)

  • 100% covered health coverage for you, and 90% for your dependents.
  • 100% covered Life & AD&D, and short-term disability coverage for you.
  • 401(k) with 3% matching.
  • Continued education and professional development.
  • We are aggressive with our goals and hence speed with predictability are critical when it comes to execution. Symbl’s fixed leave policy of 18 Planned vacation days, 8 sick days, generous maternity, paternity and 16 annual holidays - are carefully curated to deliver on those core company values.

About Symbl.ai
We are a venture-funded AI startup building conversational AI since 2018; and the journey of building safe, secure and business-ready AI to solve problems in communication experiences informs a lot of the decisions we make about how we build our technology. Symbl is a developer-first platform whose core mission is to bring understanding and generative AI to every business that  relies on understanding human conversations, and give machines the ability to comprehend communications better than humans. We believe this will transform how businesses think about their knowledge and will accelerate the various use cases where unlocking unstructured data for business use cases generates ROI at scale.
We obsess about a great developer experience for all our products, the business-readiness of the AI we build, and pride ourselves in bringing state-of-the-art Large Language Models (LLMs) to multi-modal multi-party conversations. 

As an organization, we firmly believe in equal opportunity and do not engage in any form of discrimination based on race, religion, national origin, gender, sexual orientation, age, veteran status, disability, or any other legally protected status. We are committed to maintaining a diverse and inclusive work environment where every individual is respected and valued for their unique contributions.
How to Apply:  Email with your cover letter including any relevant links to Github or your recent publications to [email protected]. We look forward to getting to know you!

What you need to know about the Austin Tech Scene

Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.

Key Facts About Austin Tech

  • Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
  • Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
  • Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
  • Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
  • Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center

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