Picture yourself here.
LMNT is an early-stage venture-backed AI speech synthesis startup. Our team is obsessed with creating natural, expressive, life-like voice experiences using deep learning as our technology backbone. In previous lives, we have built, productionized, and shipped consumer electronics (e.g. Google Glass), search advertising, and machine virtualization products. We're drawn to hard problems – these seem to be a daily occurrence in our line of work. :)
You can see some of our work in our Github repositories.
As a Software Engineer, you would develop internet-scale data pipelines, and serve, scale, and optimize AI models.
- Contribute to the technical development of LMNT's AI speech synthesis product
- Assist in constructing large-scale data pipelines and designing supporting infrastructure
- Contribute to the creation and execution of ML roadmaps in collaboration with the product team
- Collaborate with a team of engineers and product folks
- Knowledge of machine learning frameworks (e.g., PyTorch, ONNX)
- Familiarity with reactive web frameworks (e.g., Vue.js)
- Understanding of hardware architectures and instruction sets (e.g., NVIDIA PTX, ARM NEON)
Signs you’re a great fit:
- Excellent coding skills, particularly in structural and algorithmic code
- Ability to work effectively in ambiguous situations
- Continuous learner; able to evaluate and acquire new skills/tools as needed
- Willingness to participate in product decisions and explore new directions
- Attention to detail in product and engineering design
- Love puns, jokes, and solving hard problems
- Experience in scaling a codebase
- Experience in productionized machine learning systems
- Knowledge of hardware architectures and instruction sets (e.g., NVIDIA PTX, ARM NEON)
Come work with us!
Send your résumé or LinkedIn URL via email. Suitable candidates will be contacted within a few days.
Note: We value diverse perspectives. If you have a passion for speech synthesis and are willing to learn, we encourage you to apply even if you don’t meet the preferred skills.