Senior Machine Learning Engineer

Jobtailor; São Paulo; Presencial; BRL 180 000 - 320 000; Tempo integral

Resumo da oferta

Jobtailor is seeking a senior ML engineer to design, validate, and productionize ML models and pipelines on Vertex AI within a data-driven team.

You will implement training, deployment, monitoring, and experiments, collaborating with data scientists and engineers to deliver scalable Python code and TensorFlow models in containerized services.

Qualificações

• Advanced experience with Vertex AI for ML lifecycle management (Pipelines, Registry, Feature Store).
• Strong knowledge of the GCP data ecosystem for feature engineering and processing.
• Proficiency in Python; knowledge of R and PySpark is desirable.
• Deep practical understanding of TensorFlow and modern ML frameworks.
• Strong ability to create and interpret statistical models and ML algorithms.
• Experience with Docker and Kubernetes for containerization and orchestration.
• Experience developing REST APIs and using CI/CD tools (e.g., Jenkins, Git).
• Familiarity with experiment tracking tools (MLflow or Vertex AI Experiments).
• Strong SQL; NoSQL experience (e.g., MongoDB).
• Hands-on experience with Agile methodologies and English language skills.
• Google Cloud Professional ML Engineer certification held.

Responsabilidades

• Study and transform data science projects into efficient ML models.
• Develop and improve model pipelines (development, deployment, monitoring).
• Research and implement ML algorithms and tools.
• Assist with and improve notebooks/code handling large real-world data.
• Contribute to data selection and representation methods for models.
• Research and develop design, testing, and deployment of optimization and deep learning algorithms.
• Develop and validate control and monitoring of algorithms in production.
• Conduct analyses to understand data science aspects; knowledge of Docker.

Conhecimentos

Python Proficiency

TensorFlow Knowledge

Statistical Models

English Proficiency

Agile Methodologies

Formação académica

Google Cloud Professional ML Engineer Certification

Ferramentas

Vertex Pipelines

Vertex Model Registry

Vertex Feature Store

Docker

Kubernetes

MLflow

Jenkins

Git

CI/CD Tools

PySpark

REST APIs

MongoDB

Descrição da oferta de emprego

• • Study and transform data science projects into efficient machine learning models
• • Develop and improve model pipelines (development, deployment, and monitoring)
• • Research and implement machine learning algorithms and tools
• • Assist with and continuously improve existing notebooks/code and workflows handling large volumes of real-world data to enhance their performance
• • Contribute to and validate research and selection of appropriate data for models, as well as the best methods for data representation
• • Research and develop the design, development, testing, and deployment of optimization algorithms, deep learning, and robotics/AI
• • Develop and validate control and monitoring of algorithms and models in production
• • Conduct and validate studies and analyses to understand various aspects of data science. Knowledge of Docker.

Requirements

• Advanced experience with the Vertex AI ecosystem for ML lifecycle management (Vertex Pipelines, Vertex Model Registry, Vertex Feature Store)
• Strong knowledge of the GCP data ecosystem for feature engineering and distributed processing
• Proficiency in Python (knowledge of R and PySpark/Spark is highly desirable)
• Deep practical understanding of TensorFlow and modern Machine Learning frameworks
• Strong knowledge in creating/understanding statistical and mathematical models and Machine Learning algorithms
• Experience with containerization using Docker and microservices orchestration with Kubernetes
• Experience developing REST APIs and using CI/CD tools (e.g., Jenkins, Git)
• Familiarity with experiment tracking tools (such as MLflow or Vertex AI Experiments)
• Strong SQL query skills and experience with NoSQL databases (such as MongoDB)
• Practical experience working with Agile methodologies
• Advanced English (technical reading, writing, and speaking)
• Official Google Cloud Professional Machine Learning Engineer certification
• Practical experience with GenAI within Vertex AI (using Model Garden, tuning LLMs such as Gemini)

Core Competencies

Demonstrates expertise in developing and optimizing machine learning models and pipelines, with a strong focus on the Vertex AI ecosystem and GCP data tools. Proficient in Python and TensorFlow, with experience in containerization and CI/CD practices.

Highest-signal resume keywords

• Vertex AI Ecosystem
• Machine Learning Frameworks
• Python Proficiency
• Docker Containerization
• Google Cloud Professional Machine Learning Engineer Certification

ATS Optimization Keywords

Hard Skills

• Machine Learning Algorithms
• Statistical Models
• TensorFlow
• SQL Query Skills
• NoSQL Databases
• REST API Development
• CI/CD Tools
• Feature Engineering
• Optimization Algorithms
• Deep Learning

Soft Skills

• Technical Communication
• Collaboration

Certifications & Qualifications

• Google Cloud Professional Machine Learning Engineer Certification

Industry Keywords

• Data Science
• Machine Learning
• AI
• Model Deployment
• Experiment Tracking

Tools & Technologies

• Vertex Pipelines
• Vertex Model Registry
• Vertex Feature Store
• Docker
• Kubernetes
• MLflow
• Jenkins
• Git
• Agile Methodologies
• GenAI