Cloud Solution Engineer

Oracle; São Paulo; Presencial; BRL 60.000 - 90.000; Tempo integral

Resumo da oferta

A leading consulting firm is seeking an AI Cloud Solution Engineer I to join their dynamic team in São Paulo. This exciting role involves developing AI algorithms, integrating solutions, and collaborating across teams to address real-world challenges. Candidates should have a strong background in computer science, mathematics, and a commitment to continuous learning.

Qualificações

• Strong academic record
• Knowledge of Vector Calculus and Linear Algebra
• Commitment to continuous learning

Responsabilidades

• Assist in the development and implementation of AI algorithms on cloud platforms
• Support integration of AI solutions with existing systems
• Deploy and maintain AI models in production environments

Conhecimentos

Programming

Data Analysis

Machine Learning

Cloud Computing

Algorithms

Formação académica

B.S in Computer Science or similar fields

Ferramentas

TensorFlow

PyTorch

scikit-learn

Descrição da oferta de emprego

Oracle is a leading consulting firm specializing in AI-driven solutions for businesses across various industries. We leverage cutting-edge technologies to help our clients optimize their operations, enhance customer experiences, and drive innovation. As part of our dynamic team, you'll have the opportunity to work on exciting projects and collaborate with industry experts to deliver impactful solutions.

Position Overview:

We are seeking a talented and passionate AI Cloud Solution Engineer I to join our consulting team. In this role, you will apply latest theories to develop new and improved products while also collaborating with peers across the organization. You will be collaborating with cross-functional teams to integrate autonomous functionality into products and platforms that solve real-world business challenges.

Qualifications

Career Level - IC2

Responsibilities

Key Responsibilities:

- Assist in the development and implementation of AI & Mathematical algorithms and models on cloud platforms.

- Support the integration of AI solutions with existing systems and applications, ensuring seamless functionality and performance.

- Assist in the deployment and maintenance of AI models in production environments, monitoring performance and optimizing as needed.

- Implement data analysis through statistical programming; Question and/or challenge design according to scientific questions.

- Stay updated on the latest advancements in AI, mathematics, cloud computing, and related technologies, and contribute insights to enhance our offerings.

- Develop system models to communicate advanced concepts to customers, stakeholders and developers.

What requirements should you have?

- Have a B.S in computer science, mathematics, statistics or similar fields.

- Vector Calculus; Probability & Linear algebra theory knowledge.

- Strong academic record.

- Strong commitment to continuous learning.

- Excellent programming and debugging skills in one or more languages like Python, C, or C++.

- Design, develop, test, deploy, maintain, and enhance large scale software solutions.

- ML design and optimizing ML infrastructure knowledge-- model deployment, model evaluation, data processing, debugging, fine tuning.

- Familiarity with cloud computing platforms.

- Maintain and develop core algorithms.

- Develop AI models that are trustworthy, safe, and reliable, especially in high-stakes scenarios..

- Any previous knowledge about the topics below is a plus.

What other requirements should you have?

- Algorithms-- Network algorithms, scheduling, searching, sorting and string processing.

- Background of theory and practice of Bayesian models and statistics.

- Experience in creating implementations of deep learning algorithms.

- Experience with AI frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn is a plus.

- Linear/Quadratic optimization & Polytopes knowledge.

- Scientific Computing theory knowledge-- Interpolation and approximation of functions; Numerical methods for Differential Equations.

- Theory of computation knowledge-- Formal language theory, computability theory, and complexity theory.