Applied Machine Learning Researcher

Posted 5 months agoViewed

📍 Location: West Coast, Central Europe, PST, CET

🔍 Industry: Machine Learning / AI

🏢 Company: Gensyn👥 1-10💰 $43,000,000 Series A almost 2 years agoCryptocurrency Blockchain Machine Learning

🪄 Skills: PythonSoftware DevelopmentArtificial IntelligenceKerasMachine LearningNumpyPyTorchAlgorithmsData scienceGoPandasTensorflowCommunication SkillsAnalytical SkillsCollaboration

Requirements:

Strong background in applied machine learning / engineering.
Hands-on experience with distributed model training.
Comfortable in an applied research environment with high autonomy.
Excellent verbal and written communication skills.

Responsibilities:

Pursue novel research by building scalable, distributed models over decentralised infrastructure.
Partner with researchers and engineers to run experiments from theory to production.
Maintain experimental frameworks and test benches for ML research in high-scale settings.
Follow best practices in coding, testing, and documentation.

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🔥 Sr. Applied Machine Learning Researcher - Generative Models (US Remote)

Posted 1 day ago

📍 United States

🧭 Full-Time

💸 170734.0 - 213418.0 USD per year

🔍 Software Development

🏢 Company: Splice👥 101-250💰 $55,000,000 Series D about 4 years agoMedia and Entertainment Music Machine Learning Software

🔧 Requirements

Ph.D. or Master's degree in Electrical Engineering, Computer Science or related Engineering discipline.
Background or proven experience in Digital Signal Processing.
Proven experience (2+ years) in an Applied Research role focused on Latent Diffusion based generative models for audio and/or symbolic music generation using Transformer-based architectures.. Alternatively, solid experience with diffusion-based models in the image domain, would be considered.
Proficiency in Python and deep learning frameworks (e.g., TensorFlow, PyTorch).
Familiarity with software development best practices and version control systems (e.g., Git).
Strong communication and collaboration skills, with the ability to work cross-functionally with stakeholders in Engineering, Product and Design.

💡 Responsibilities

Conduct literature research and experimentation in the field of ML-based generative audio using Latent Diffusion and symbolic music generation using Transformer-based architectures.
Collaborate with our ML Engineers to design performant model architectures for efficient ML-based audio synthesis and symbolic music generation, as well as adapting and fine-tuning existing models.
Develop proof-of-concept prototypes to showcase and validate capabilities and use cases using generative audio/symbolic models.
Engage with academic and open source communities to stay up to date with the latest developments in the space, collaborate in joint projects, and identify top talent for our AI & Audio Science team’s future hiring needs.
Stay up-to-date with the latest academic and industrial research in generative models for music, incorporating relevant findings into our applied research and product development processes.
Document research findings, methodologies, and best practices. Collaborate with team members to disseminate knowledge and insights.

PythonSoftware DevelopmentSQLData AnalysisGitImage ProcessingMachine LearningNumpyPyTorchAlgorithmsData StructuresTensorflowCommunication SkillsCollaborationCI/CDRESTful APIsDocumentationPrototypingSoftware Engineering

Posted 1 day ago

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