Senior Software Developer, ML Engineer

SiDi

Engenheiro de ML no SiDi, instituto brasileiro de ciência e tecnologia, desenvolvendo modelos embarcados para edge computing e smartphones. Otimizando, integrando e monitorando modelos em produção com pipelines de MLOps.

Posted 8/10/2026full-timeManaus • 🇧🇷 BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and optimizing machine learning models for resource-constrained devices, with a strong focus on MLOps practices and model optimization techniques. Proficient in Python and familiar with embedded systems, ensuring efficient integration and deployment of predictive models.

Highest-signal resume keywords

Machine Learning Model DevelopmentMLOps ImplementationPython ProgrammingEmbedded Systems KnowledgeModel Optimization Techniques

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData ScienceModel CompressionQuantizationTensorFlow LiteExecuTorchONNX RuntimeData StructuresAlgorithmsGit Version Control

Soft Skills

CollaborationCommunication

Tools & Technologies

NumPyPandasScikit-learnTensorFlowPyTorchKubeflowMLflowDVC

Certifications & Qualifications

Master's Degree in ML/AI

Industry Keywords

Edge ComputingMobile DevelopmentData TransformationConcept Drift MonitoringSignal Processing

Tech Stack

Tools & technologies

AndroidKotlinNumpyPandasPythonPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

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
Perform extraction, transformation, and analysis of data from mobile application logs and propose new data collection if 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 deployed models, proposing retraining and updates

Requirements

What you’ll need

Proven experience (2 to 4 years) in data science with a focus on applied machine learning
Solid programming fundamentals, including data structures, algorithms, Git version control, and writing clean code
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, or ExecuTorch
Good understanding of embedded systems and hardware constraints (memory, CPU, battery)
Degree in Computer Science, Computer Engineering, Electrical Engineering with emphasis on embedded systems, Data Science, or related fields
Advanced English for reading, writing, and conversation
Familiarity with mobile development (Android/Kotlin) to support integration is a plus
Practical knowledge of model optimization for the edge (pruning, quantization, knowledge distillation) is a plus
Experience with MLOps frameworks (Kubeflow, MLflow, DVC) is a plus
Knowledge of signal processing (audio, accelerometer, gyroscope) for mobile device models is a plus
Familiarity with deployment across heterogeneous environments (ARM, mobile GPU, DSP) is a plus
Master's degree or postgraduate studies in ML/AI will be considered a plus

Benefits

Comp & perks

40-hour work week under CLT (Brazilian employment regime)
Flexible hours with hybrid work (4 days in the office and 1 day remote)
Gympass (WellHub)
Workplace exercise sessions
Quick massage
Psychological support
Health and dental insurance for you and your family
Childcare assistance
120-day maternity leave
Extended paternity leave
Private pension plan
Support program for continuing education and specialization
Support for our SiDiers to become fluent in other languages
Weekly lecture series on global trend topics
Flexible Meal and Food Vouchers
Commuting subsidy to SiDi
Parking available for on-site employees
Annual performance bonus
Awards for SiDiers who do something outstanding
Committees on Well-being, Diversity, Mental Health, Social Initiatives, Sustainability, and Women's Inclusion in Technology
Relaxed, collaborative environments with communal areas, a decompression room, kitchen, and coffee machine
Numerous partner discounts and benefits
Equal opportunity environment
Position available for candidates with disabilities