Data Scientist Leader

Há 4 dias

Região Geográfica Intermediária de São Paulo, Brasil beBeeMachine Tempo inteiro US$100.000 - US$120.000
Senior Machine Learning Architect

Job Summary:

We are seeking a Senior Machine Learning Architect to design and build large-scale architectures, workflows, tools, and automation for processing data. As a machine learning engineer, you will apply your expertise to solve global business challenges with a focus on making tasks easier for data scientists.

Key Responsibilities:

  • Architect and develop end-to-end machine learning solutions using cloud platforms like AWS or GCP.
  • Manage and automate the machine learning lifecycle, ensuring seamless integration with other technical teams.
  • Collaborate with data engineers and data scientists to create highly scalable solutions that meet business requirements.
  • Evaluate the performance and cost of potential architectures, optimizing resources for maximum efficiency.
  • Understand the software development life cycle to integrate machine learning solutions with other technical areas.
  • Interact with stakeholders to understand business challenges and propose innovative solutions.
  • Communicate and teach others how to use machine learning developments effectively.

Requirements:

  • Bachelor's Degree in Computer Science, Engineering, or a related field.
  • 5+ Years of experience implementing and deploying machine learning solutions.
  • 5+ Years of advanced Python programming experience, including knowledge of libraries like NumPy and pandas.
  • 3+ Years of experience working with SQL and Spark, including data warehousing and ETL processes.
  • 3+ Years of experience working in cloud environments (AWS or GCP), including cloud security and compliance.
  • Knowledge and hands-on experience with containerization tools (e.g., Docker) and orchestration tools (e.g., Kubernetes).
  • Experience with version control systems, preferably Git, and workflow orchestration tools like Airflow.
  • Knowledge of data architectures and systems integration, including experience with big data technologies like Hadoop and NoSQL databases.
  • Ability to troubleshoot and solve complex software system issues independently.
  • Experience automating machine learning lifecycles and managing end-to-end ML solutions, including deployment and monitoring.
  • Experience with scripting in Bash or similar shell environments, including automation and data processing.
  • Familiarity with FastAPI or similar web frameworks for serving ML models, including RESTful APIs and API gateways.
  • Experience with AWS SageMaker Studio and infrastructure-as-code tools such as CloudFormation.
  • Understanding of software development life cycle (SDLC) and ability to integrate ML solutions with other technical teams.
  • Strong communication skills with the ability to teach and explain technical solutions to different stakeholders.
  • Advanced English Level is required for this role as you will work with US clients. Effective communication in English is essential to deliver the best solutions to our clients and expand your horizons.

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