MLOps Engineer
São Paulo, State of São Paulo, Brazil - Remote
Xenon7 is an inferno where skill, dedication, and passion run together.
Are you curious-minded and passionate about pushing the boundaries of technology? Do you dream of using AI to address the world's most pressing challenges, from healthcare to education, energy, or food security? Whether you're a professor, technologist, scientist, or someone brimming with creative potential, we invite you to explore career opportunities at the forefront of AI innovation.
Job Summary
Xenon7 is a Consulting company focused on helping companies understand Data, AI, and ML space and implement solutions and strategies based on these technologies in the best possible way while also applying AI ethics and Infosec Regulations and Principles. We bring in rich experience in various industries and technology capabilities including Healthcare and Life Sciences, Financial Services, Retail, CPG, Media, and others.
You will be part of a team deploying state-of-the-art AI solutions for our clients. Each project will have its own ML/DS solution which needs to be deployed so that it keeps the best performance. On top of that, the solution needs to be continuously monitored, reliable, and easy to upgrade.
Responsibilities:
As MLOps your responsibilities include but are not limited to:
- Deploying and operationalizing MLOps, in particular, implementing:
- Model hyperparameter optimization
- Model evaluation and explainability
- Model training and automated retraining
- Model workflows from onboarding, operations to decommissioning
- Model version tracking & governance
- Data archival & version management
- Model and drift monitoring
- Creating and using benchmarks, metrics, and monitoring to measure and improve services.
- Providing best practices and executing POC for automated and efficient model operations at scale.
- Designing and developing scalable MLOps frameworks to support models based on client requirements.
- Being the MLOps expert for the sales team, providing technical design solutions to support RFPs.
- Establish and maintain relationships with third parties/vendors
- Create and maintain comprehensive project documentation
Engagement:
This will be a B2B contract engagement and we are open to discussing different levels of commitment from hourly/part time to full-time.
Requirements
- 5+ years of experience in Software Engineering, DevOps, or Data Science/ML roles
- 1+ years of experience as MLOps
- Familiarity with cloud platforms like AWS, Azure, or GCP, including knowledge of services like EC2, S3, SageMaker, or Google Cloud ML Engine for scalable and efficient model deployment.
- Experience with Docker and container orchestration platforms like Kubernetes.
- Experience with Quality Assurance using experiment tracking and workflow versioning.
- Proficiency in data ingestion, pipelines, transformation, and storage technologies (e.g., SQL, NoSQL, Hadoop, Spark).
- Experience with machine learning frameworks such as PyTorch, TensorFlow, and TFX.
- Knowledge of version control (e.g., Git), CI/CD tools (e.g., Jenkins), and infrastructure automation (e.g., Ansible, Terraform)
- Experience with unit/integration testing and monitoring tools (e.g., Prometheus, ELK Stack) and logging frameworks (e.g., Logstash, Fluentd)
- A strong sense of teamwork and communication skills to collaborate with data scientists, engineers, and stakeholders
Benefits
- Work From Home
- Performance Bonus
- Training & Development
- Meet and collaborate with other extremely smart people
- Meet and work with CIOs, CTOs, and other important people from big companies
- Work on exciting cutting-edge projects
- Diversity: work on dozens on different AI projects and applications each year
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Ansible AWS Azure CI/CD Consulting DevOps Docker EC2 ELK Engineering GCP Git Google Cloud Hadoop Kubernetes Logstash Machine Learning MLOps Model deployment Model training NoSQL Pipelines PyTorch SageMaker Security Spark SQL TensorFlow Terraform Testing
Perks/benefits: Career development
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