Design, develop, and deploy scalable AI/ML solutions across the healthcare domain.
Responsibilities
Design, develop, and deploy scalable AI/ML solutions across healthcare domain
Select, implement, and optimize supervised and unsupervised learning algorithms for classification, regression, clustering, anomaly detection, and forecasting
Learn and adopt AIDLC as the standard development approach, and promote its adoption through training and knowledge sharing
Develop deep learning, NLP, computer vision, recommender-system, reinforcement-learning, and generative AI models based on business needs
Perform feature engineering, hyperparameter tuning, cross-validation, error analysis, and model comparison using appropriate evaluation metrics
Lead data science initiatives for advanced electronics and high‑tech industries, collaborating with cross‑functional teams to develop models, analytics, and insights.
Responsibilities
Develop and deploy predictive models using machine learning techniques
Prepare and clean data for analysis
Create descriptive plots and reports
Collaborate with data engineering and software development teams
Lead the Data Science team, driving high-impact projects, mentoring staff, and shaping the technical direction of data science and machine learning solutions.
Locations (2)
São Paulo, Brazil
Brazil
Compensation
Competitive salary
Profit sharing
Responsibilities
Manage a team of Data Scientists and Machine Learning Engineers
Act as a technical reference, architecting, developing, and deploying machine learning systems
Discuss business requirements with Product Managers and senior leaders
Guide the team in designing and executing experiments
Recruit and develop talent
Requirements
MSc. or PhD in Computer Science, Statistics, or a relevant technical field
Nice to have: Large Language Models (RAG, fine-tuning)
Nice to have: AI agents or agentic frameworks (LangGraph, LangChain)
Nice to have: experience with fast-growing startups or high-tech companies
The starting pay range for this role is $70/Hr to $80/Hr.
Responsibilities
Partner with an assigned CIO organization as a primary AI/ML engineering lead, converting business problems into measurable machine learning and generative AI use cases.
Design, develop, test, deploy, and support production-grade solutions spanning predictive machine learning, deep learning, large language models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI.
Prepare and analyze structured and unstructured data using Python, NumPy, Pandas, Matplotlib, and Seaborn; perform data quality analysis, preprocessing, feature engineering, and exploratory analysis.
Develop supervised and unsupervised learning solutions using techniques such as linear and logistic regression, decision trees, random forests, gradient boosting/XGBoost, support vector machines, K-Means, DBSCAN, PCA, and other dimensionality-reduction methods.
Build deep learning solutions with PyTorch (preferred) or TensorFlow/Keras, applying neural networks, CNNs, RNNs/LSTMs, transformers, attention mechanisms, and transfer learning where appropriate.
Requirements
Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics, or a related field, or equivalent practical experience.
