About the Role
We are seeking a talented MLOps Engineer (Python, AWS) - Remote to join our dynamic team. In this role, you will be responsible for developing and maintaining machine learning operations, ensuring the smooth deployment and monitoring of ML models in production. As an MLOps Engineer, you will work closely with data scientists and software engineers to create robust ML pipelines that drive our AI initiatives.
What You'll Do
- Design and implement scalable ML pipelines using Python and AWS services.
- Collaborate with data scientists to deploy machine learning models into production environments.
- Utilize tools like Docker, Kubernetes, and Terraform for containerization and orchestration.
- Monitor and optimize the performance of ML models in production.
- Develop and maintain CI/CD processes for ML workflows.
- Work with real-time data pipelines and ensure data quality and integrity.
- Implement automation tools for MLOps to streamline workflows.
- Participate in project management activities to ensure timely delivery of AI projects.
Requirements
- 3+ years of experience as an MLOps Engineer or in a similar role.
- Strong proficiency in Python and experience with AWS services.
- Hands-on experience with MLOps platforms and automation tools.
- Familiarity with Kafka for data streaming and processing.
- Experience with AI chatbots or retrieval-augmented generation (RAG) systems is a plus.
- Knowledge of data engineering principles and practices.
- Experience with CI/CD tools and methodologies.
- Excellent problem-solving skills and ability to work in a collaborative environment.
Nice to Have
- Experience with Ruby, MySQL, Kotlin, React, or TypeScript.
- Familiarity with FastAPI for building APIs.
- Understanding of big data technologies and frameworks.
What We Offer
- Competitive salary ranging from $120,000 to $150,000 per year.
- Fully remote work environment with flexible hours.
- Opportunities for professional development and growth.
- Health and wellness benefits.
- Collaborative and innovative team culture.
- Access to the latest tools and technologies in AI and ML.
- Support for work-life balance and employee well-being.
This MLOps Engineer role offers a competitive salary, remote work flexibility, and the opportunity to work on cutting-edge AI projects.
Who Will Succeed Here
Proficient in Python and experienced with MLOps tools such as Kubeflow and MLflow, enabling the seamless integration of machine learning models into production environments.
Ability to manage infrastructure using AWS services like S3, EC2, and Lambda, along with CI/CD practices to automate deployment processes, which is crucial for a remote working environment.
Hands-on experience with container orchestration using Docker and Kubernetes, coupled with a mindset focused on continuous improvement and scalability of ML pipelines.
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