The Senior Machine Learning Engineer is pivotal in shaping the future of our Automated Speech Recognition (ASR) technologies. The role is at the forefront of developing a sophisticated, scalable ASR service designed for a diverse range of clients. This role involves not just the creation of machine learning models but also their personalization and deployment, ensuring that our ASR solutions are not only cutting-edge but also finely tuned to the specific needs of each user. The position's expertise guides the team in building a platform that is robust, efficient, and at the vanguard of speech technology.
In this role, you will:
- Lead the architectural design and development of our comprehensive ASR service platform.
- Mentor and guide a team of talented machine learning engineers, fostering a culture of innovation and excellence.
- Collaborate closely with cross-functional teams, including product management and software engineering, to deliver integrated and effective solutions.
- Partner with systems and infrastructure teams to engineer production-grade deployments of models at scale.
- Spearhead research into novel machine learning techniques and their application to our ASR systems.
- Ensure the reliability, scalability, and performance of the ASR service, from development through to production.
- Drive the strategic direction of our ASR technology, aligning it with the company's long-term goals.
We would love to hear from you if:
- You have a M.S. or Ph.D. in Computer Science, Electrical Engineering, or a related field.
- You have a minimum of 10 years of hands-on experience in machine learning, with a significant focus on ASR.
- You have expert-level proficiency in Python and deep familiarity with machine learning frameworks such as TensorFlow or PyTorch.
- You have a deep understanding of the latest tools, standards, and best practices in software and model development.
- You have demonstrated experience in handling large-scale data processing and deploying machine learning models in cloud environments (e.g., AWS, GCP, Azure).
- You have familiarity with cloud technologies and MLOps principles, including Kubernetes and Docker.
- You have proven leadership capabilities and exceptional communication skills, with the ability to articulate complex technical concepts to a broad audience.