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Heinrich Lenz

Heinrich Lenz

AI Training Specialist for Custom LLM for Audiovisual Installation

Germany flagBerlin, Germany
IntermediateOther

Key Skills

Software

Other

Top Subject Matter

Audiovisual Installation/Language Modeling
Generative/Audio Modeling
MIDI Transformer Network/Live Audio AI

Top Data Types

TextText
AudioAudio
VideoVideo

Top Task Types

Fine-tuningFine-tuning

Freelancer Overview

AI Training Specialist for Custom LLM for Audiovisual Installation. Brings 16+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Master of Arts, Folkwang University of the Arts (2024) and ERASMUS Exchange, Guildhall School of Music & Drama (2020). AI-training focus includes data types such as Text and Audio and labeling workflows including Fine-tuning.

Intermediate

Labeling Experience

AI Training Specialist for Custom LLM for Audiovisual Installation

OtherTextFine Tuning
Trained a custom small-scale language model for a live audiovisual installation exploring language acquisition and loss. Developed data pipelines and conducted hands-on AI training with human-in-the-loop methods. Integrated the model into a live performance with iterative evaluation cycles. • Tasked with creating and curating text datasets for LLM training. • Performed ongoing model fine-tuning to tailor linguistic output for installation needs. • Used Python and PyTorch for model development and training routines. • Collaborated with artists and technologists in a performance-installation context.

Trained a custom small-scale language model for a live audiovisual installation exploring language acquisition and loss. Developed data pipelines and conducted hands-on AI training with human-in-the-loop methods. Integrated the model into a live performance with iterative evaluation cycles. • Tasked with creating and curating text datasets for LLM training. • Performed ongoing model fine-tuning to tailor linguistic output for installation needs. • Used Python and PyTorch for model development and training routines. • Collaborated with artists and technologists in a performance-installation context.

2026 - 2026

AI Training Specialist for Real-Time MIDI Generation

OtherAudioFine Tuning
Designed and trained a transformer-based AI model for real-time generative MIDI audio output used in live settings. Curated and annotated MIDI datasets to optimize model learning and responsiveness. Conducted iterative training, evaluation, and adjustment cycles for live music applications. • Handled dataset preparation and annotation for generative MIDI modeling. • Used Max/MSP, ml.*, and Ableton Live as primary AI and audio tools. • Focused on real-time, live performance integration of AI-generated outputs. • Evaluated model outputs in situ with continual refinement.

Designed and trained a transformer-based AI model for real-time generative MIDI audio output used in live settings. Curated and annotated MIDI datasets to optimize model learning and responsiveness. Conducted iterative training, evaluation, and adjustment cycles for live music applications. • Handled dataset preparation and annotation for generative MIDI modeling. • Used Max/MSP, ml.*, and Ableton Live as primary AI and audio tools. • Focused on real-time, live performance integration of AI-generated outputs. • Evaluated model outputs in situ with continual refinement.

2025 - 2025

AI Training Specialist for RAVE Model Audio Installation

OtherAudioFine Tuning
Trained a RAVE model using custom audio datasets for generative audio in an installation context. Prepared and curated datasets and managed iterative data annotation for improving audio generation quality. Oversaw deployment and evaluation of the trained model within an art installation. • Managed labeling of audio files for model training and evaluation. • Performed quality control and feedback-driven data adjustments. • Utilized RAVE and Max/MSP for the training environment. • Focused on generative sound output in a live exhibition setting.

Trained a RAVE model using custom audio datasets for generative audio in an installation context. Prepared and curated datasets and managed iterative data annotation for improving audio generation quality. Oversaw deployment and evaluation of the trained model within an art installation. • Managed labeling of audio files for model training and evaluation. • Performed quality control and feedback-driven data adjustments. • Utilized RAVE and Max/MSP for the training environment. • Focused on generative sound output in a live exhibition setting.

2025 - 2025

Education

F

Folkwang University of the Arts

Master of Arts, Music

Master of Arts
2021 - 2024
H

Hochschule für Musik Franz Liszt

Bachelor of Arts, Electroacoustic Composition

Bachelor of Arts
2016 - 2021

Work History

S

Self-Employed

Freelance Audio Engineer, Musician, and Curator

Berlin
2024 - Present
S

Self-Employed

Media Arts Project Manager

Berlin
2022 - Present