At the company, we are committed to innovation in engineering, AI, and robotics. Our new Data Intelligence team is crucial to this mission, shaping our future through data. We blend creativity and precision to power intelligent products and create data strategies and pipelines for the next generation of connected devices.
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We are seeking a specialized Lead Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labeling pipelines. The main objective is to reduce reliance on manual annotation through techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will ensure the transition from raw data collection to model-ready datasets, providing high-quality labels at scale.
Key Responsibilities:
- Design and deploy automated labeling systems.
- Develop "Human-in-the-Loop" (HITL) systems.
- Implement quality assurance and denoising algorithms.
- Collaborate with software engineers to integrate labeling tools with existing data lakes and ML training infrastructure.
- Optimize models for quality pseudo-label generation.
- Maintain robust data preparation infrastructure.
- Perform data visualization and in-depth analysis using advanced techniques.
- Collaborate with Data Scientists, Software Engineers, and product teams for high data quality and usability.
About You:
- At least 8+ years of experience in Machine Learning engineering, focused on data-centric AI or computer vision/NLP pipelines.
- Proficiency in Python with mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).
- Proven experience with automating labeling processes and managing large-scale unstructured data.
- Familiarity with cloud infrastructure (AWS, GCP, Azure).
- Experience with version control for datasets.
- Strong background in feature engineering, data analysis, and visualization.
Education Requirements:
Bachelor’s or Master's degree in Computer Science, Engineering, Mathematics, Data Science, or a related field.
The company is an equal opportunities employer, welcoming diversity in our workforce.
