About Valyant AI:
At Valyant AI, we are building the future of work using the latest AI technologies to simplify the lives of front line workers. We are currently expanding our order-taking AI with several major restaurants and we are building new products to support back of house restaurant staff. You can find examples of our platform at valyant.ai.
Why Valyant AI:
We’re working on something that does not exist and inventing new solutions every day
Collaborative and engineering forward organization where every engineer contributes to the success of our products
We work in an agile environment and every day you’ll be presented with extremely difficult and intellectually challenging problems
Responsibilities:
Develop and implement state-of-the-art machine learning models for Automatic Speech Recognition (ASR) or Natural Language Processing (NLP) applications
Collaborate with engineers to collect, process and curate large datasets to train and fine-tune machine learning models
Work with software engineers to build data pipelines and feedback loops
Continuously optimize and improve existing ML models for enhanced performance, accuracy, and efficiency
Work closely with software engineers to integrate machine learning models into our applications
Support machine learning models in production
Evaluate, test, and validate ML models to ensure robustness and reliability in real-world scenarios
Document everything to support the team's understanding of processes, data and technology
Stay up to date on the latest advancements in machine learning, ASR, NLP and LLMs to incorporate cutting-edge techniques into our technology stack
Qualifications:
Education: Bachelor's or Master's degree in Computer Science, Mathematics, Physics, or a related field.
Experience: Minimum of 2 years of industry experience in machine learning with a focus on either Automatic Speech Recognition (ASR) or Natural Language Processing (NLP).
Skills:
Proficient in Python, SQL and working with Notebooks
Familiarity with ML tooling and frameworks such as Pandas, PyTorch, TensorFlow, or Keras
Understanding of MLOps workflows
Basic understanding of containerization using Docker
Bonus points for experience with any of the tools we use: AWS (SageMaker, BedRock, S3, MTurk, ECS), mySQL, GRPC, Elasticsearch, MLFlow, GitHub, Terraform
Curious, self-starter and able to work independently
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