ML Engineer
Catalyst Labs, LLC
About the job ML Engineer
Our Client
- Design, build, and deploy production-grade ML systems with end-to-end ownership of the model lifecyclefrom conception to deployment and maintenance.
- Architect and deliver AI-powered solutions enabling natural speech interaction and real-time audio understanding.
- Develop and optimize ML models focused on audio data to extract business-critical insights from previously unstructured voice data.
- Build agents capable of operating natively on real-world audio inputs.
- Collaborate with cross-functional teams to shape the foundations of the AI stack, improve tooling, and drive innovation in LLM and audio ML applications.
- Work directly with customers to identify needs, gather feedback, and deliver impactful real-world solutions.
- Handle the entire AI lifecycle, including data acquisition, preprocessing, model training, deployment, inference, and monitoring in production environments.
- Participate in continuous improvement of the ML infrastructure and processes for scalability and performance.
- Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
- 1-6 years of professional experience in ML engineering.
- Strong programming skills in Python (TypeScript experience is a plus).
- Hands-on experience with ML frameworks such as PyTorch or TensorFlow.
- Familiarity with cloud environments and infrastructure (preferably AWS).
- Strong understanding of data pipeline design, real-time inference, and model monitoring.
- Excellent communication skills with the ability to engage directly with customers and stakeholders.
- Proven experience building and deploying ML models into production environments.
- Demonstrated ability to own the full model lifecyclefrom data ingestion and model development to deployment and monitoring.
- Experience with audio-focused ML projects or similar domains involving unstructured data.
- Proficiency in building scalable data pipelines for model training and evaluation.
- Familiarity with FastAPI, OpenAI APIs, Baseten, LiteLLM, LiveKit, PostgreSQL, Redis, and S3 is a plus.
- Solid grasp of ML systems architecture, feature engineering, evaluation strategies, and deployment best practices.
Vacancy posted more than 2 months ago
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