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We are looking is seeking an exceptional Machine Learning (ML) Engineer to join us in shaping the future of Generative Artificial Intelligence (GenAI). As a ML Engineer, you will be an integral part of our Product Technology group, focusing on the development and deployment of generative AI models. You will collaborate closely with data scientists, software engineers, and product managers to design, implement, and optimize machine learning models that power our AI-driven products. This role offers an exciting opportunity to work with state-of-the-art technologies and make a tangible impact on the future of GenAI.
Responsibilities
Benefits
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Responsibilities
- Model Development & Optimization: design, develop, and train machine learning and algorithms models, with a focus on GenAI. Experiment with and fine-tune models to achieve optimal performance for specific applications and use cases;
- Data Pipeline Management: Build and maintain scalable data pipelines that support the training and deployment of machine learning models. Ensure data quality and integrity throughout the model development lifecycle;
- Integration & Deployment: Work closely with software engineers to integrate machine learning models into production environments. Optimize models for real-time inference, ensuring low-latency and high-throughput performance;
- Collaboration & Innovation: Collaborate with cross-functional teams to understand product requirements and translate them into technical specifications. Be the subject matter expert and stay up-to-date with the latest research in GenAI and ML, and apply new techniques to improve our products;
- Testing & Validation: Develop and implement robust testing frameworks to validate model performance and reliability. Continuously monitor and refine models in production to maintain accuracy and efficiency;
- Participate in code reviews, contribute to open-source projects, and mentor junior engineers.
- Professional experience: 2+ years in developing and implementing AI/ML models and algorithms at production level.
- Education: BSc or MSc degree in Computer Science, Data Science/Machine Learning, or a related field.
- Technology stack:
- Theoretical foundation: deep learning, traditional machine learning, probability and statistics, natural language processing, computer vision, data wrangling and preparation, and model evaluation and interpretation.
- Cloud Platforms: AWS, Azure, GCP
- Development: Python, Julia, Go/ PyTorch, Scikit-learn, Keras / CI/CD pipelines, and version control.
- MLOps practices and tools for model deployment and monitoring
- Databases: PostgreSQL, MySQL, MongoDB, Redis
- Container/Orchestration: Docker, Kubernetes, Docker Swarm
- Masters or PhD in Computer science or related technical fields.
- Problem Solving: ability to break down complex problems into manageable components, devising creative solutions, and iteratively refining ideas based on feedback and experimental evidence.
- Collaboration and Communication: proficiency in working cross-functionallycommunicating clearly, providing constructive criticism, delegating responsibilities, and respecting diverse perspectives.
- Project Management and Prioritization: demonstrated aptitude in balancing multiple projects, deadlines, and allocating time efficiently between short-term objectives and long-term goals.
- Critical Thinking: ability to carefully evaluate assumptions, questioning established methodologies, challenging own biases, and maintaining skepticism when interpreting results.
- Curiosity and Continuous Learning: ability to stay curious about advances in related fields and constantly seeking opportunities to expand knowledge base.
- Emotional Intelligence and Intellectual Humility: capable of displaying empathy, resilience, adaptability, and self-awareness. Ability to recognize own limitations, embracing uncertainty, acknowledging mistakes, and valuing others contributions.
Benefits
- Medical insurance (SulAmérica) - adding dependents will incur an additional charge;
- Meal Voucher credited at Flash Card;
- Life Insurance;
- Stock Options.
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natural language processing
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product manager
deep learning
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- Posted
- Nov 16, 2024
- Type
- Full-time
- Level
- Entry
- Location
- Brazil
- Company
- Netvagas
Industries
Human Resources Services
Categories
Engineering
Information Technology
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