Sr Data/ MLOps Engineer

Há 6 dias

São Paulo, São Paulo, Brasil InterviewHelp Tempo inteiro R$80.000 - R$150.000 por ano

Role:

Sr Data/ MLOps Engineer

Duration:
 Long-Term Contract

Location
: Brazil – Remote

We are seeking a highly motivated and experienced 
Data Engineer
 with deep expertise in the 
MLOps discipline
 to join our clients Data Engineering team. In this role, you will be responsible for designing and developing scalable, robust data architectures and MLOps solutions, leveraging the latest technologies from 
Google Cloud Platform (GCP)
 and 
AWS
.

You will collaborate closely with cross-functional teams to understand and address data and ML platform requirements while ensuring the efficient and reliable operation of our ML systems, from model development and training to deployment and inference.

Key Responsibilities

  • Design, develop, and maintain scalable, high-performance data infrastructure for real-time and batch data collection, storage, and processing.
  • Build reliable, reusable services and APIs to enable seamless data ingestion, transformation, and querying.
  • Develop software tools, products, and systems for monitoring and managing ML infrastructure and services efficiently.
  • Ensure ML systems operate optimally for model development, training, evaluation, and inference.
  • Collaborate with senior management, product teams, and other engineers to deliver high-quality data products.
  • Create tools to monitor, debug, and analyze data and ML pipelines.
  • Design and implement scalable data schemas and models.
  • Mentor team members to elevate overall technical expertise.
  • Bring innovative ideas and best practices to advance the company's position in the data and ML space.

Minimum Requirements

  • 5+ years of proven experience as a 
    Data Engineer
     or 
    MLOps Engineer
    , preferably in midsize to large data-driven companies.
  • Strong programming skills in 
    Python
     and either 
    Java
     or 
    Scala
    .
  • Hands-on experience with 
    cloud platforms
     (GCP preferred; AWS or Azure acceptable).
  • Experience with 
    BigQuery
     or similar MPP databases (e.g., Redshift, Snowflake).
  • Practical experience with 
    ML frameworks
     (TensorFlow, PyTorch) and ML deployment patterns.
  • Proficiency with 
    Docker
     and 
    Kubernetes
     for containerization and orchestration.
  • Proven experience building 
    data pipelines
     and ETL workflows.
  • Strong command-line skills and proficiency with version control (Git).
  • Excellent communication and collaboration skills.
  • Ability to work independently and quickly ramp up productivity.

Preferred Requirements

  • Knowledge of distributed data processing frameworks (Apache Kafka, Flink, Spark, etc.).
  • Experience with 
    DBT
     (Data Build Tool) and 
    Looker
    .
  • Familiarity with common ML deployment patterns.

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