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Machine Learning Engineer
Skills
Amazon Web ServicesC++DesignEnglishGoogle Cloud PlatformLarge Language ModelsLearning
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Degree in a relevant field or extensive professional experience
- Commercial machine learning research and development experience
- Hands-on experience fine-tuning and adapting large language models using LoRA QLoRA PEFT or DPO RLHF
- Experience with data training and evaluating machine learning models
- Experience with multimodal architectures such as audio-language or vision-language models
- Extensive audio and signal processing knowledge including spectral features neural codecs and generative audio models
- Experience deploying models to cloud inference on AWS or GCP with latency and cost awareness
- MLOps competency including experiment tracking model versioning evaluation pipelines and ML CI
- Experience with Python and modern ML frameworks such as PyTorch or JAX
- Excellent verbal and written English communication skills
- Excellent analytical and problem-solving skills
- Desire to innovate and push current practice
Nice to have
- Vision-language model experience
- Agile experience
- VST/AU knowledge
- Real-time audio awareness
- Commercial audio software delivery
- Sound design knowledge
- C++ reading ability
- Patent experience
Day to day
- Research and develop multimodal AI technologies that improve how people work with sound
- Build and optimise LLM-powered audio pipelines and extend a Qwen-based vision model for audio production use cases
- Design and maintain backend inference systems and collaborate with product and engineering to ship ML research into commercial products
Hiring process
- Send CV and cover letter to admin@krotosaudio.com
- Explain why you are the best candidate
- Reference the requirements above
- Include two to three brief examples of relevant results