Engineer 2, Labelling Assurance coordinating development and implementation of product labels and manuals at Cook Medical. Collaborating with various teams for timely execution of projects.
About the role
- Data Engineer integrating into SiDi team in Campinas, focused on developing machine learning models for embedded devices. Collaborating with global teams in a hybrid work environment.
Responsibilities
- Develop and optimize machine learning models for deployment on resource-constrained devices (edge computing, smartphones, and embedded systems)
- Convert, compress, and quantize models (TensorFlow Lite, ExecuTorch, ONNX Runtime) to ensure low latency and efficient memory usage
- Extract, transform, and analyze data from mobile application logs and propose new data sources when necessary
- Implement MLOps pipelines for versioning, validation, and continuous deployment of embedded models
- Collaborate with mobile development and framework teams to integrate predictive models into production
- Monitor data and concept drift in already-deployed models, proposing retraining and updates
Requirements
- Proven experience (2 to 4 years) in data science with a focus on applied machine learning
- Solid programming fundamentals (data structures, algorithms, Git version control, and clean code practices)
- Proficiency in Python and libraries such as NumPy, Pandas, Scikit-learn, and TensorFlow/PyTorch
- Experience with at least one embedded model format: ONNX, TensorFlow Lite, ExecuTorch
- Good understanding of embedded systems and hardware constraints (memory, CPU, battery)
- Advanced technical English (reading documentation, writing reports, and communicating with global teams)
- Advanced English for reading research papers and collaborating with international teams
- Basic mobile programming knowledge (Android/Kotlin) to support integration (plus)
- Practical knowledge in model optimization for the edge (pruning, quantization, knowledge distillation) (plus)
- Experience with MLOps frameworks (Kubeflow, MLflow, DVC) (plus)
- Knowledge of signal processing (audio, accelerometer, gyroscope) for models on mobile devices (plus)
- Familiarity with deploying to heterogeneous environments (ARM, mobile GPU, DSP) (plus)
Benefits
- 40-hour workweek under CLT employment, flexible hours with a hybrid setup (4 days in the office and 1 day remote)
- Gympass (WellHub), workplace stretching sessions, quick massage, and psychological support
- Medical and dental plans for you and your family
- Childcare assistance for our little SiDiers, 120-day maternity leave and extended paternity leave
- Company contributions to private pension
- Incentive program for continuing education and specialization, language fluency support, and weekly speaker series on global trend topics
- Flexible Meal and Food Vouchers
- Transportation allowance/subsidy to SiDi and parking for those working onsite
- Annual performance bonus and rewards for SiDiers who achieve outstanding results
- Committees focused on Well-being, Diversity, Mental Health, Social Impact, Sustainability, and Women's Inclusion in Technology
- Relaxed, collaborative environments with communal spaces, a decompression room, a kitchenette, and coffee machines
- Dozens of partner discounts and benefits
Job title
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Degree requirement
Tech skills
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