MLOps Engineer
Job Description
We are seeking a skilled MLOps Engineer to join our data science team at Qode. This role focuses on building, deploying, and maintaining machine learning models in production using Google Cloud Platform (GCP). The position requires expertise in software engineering, data engineering, and machine learning, with hands-on GCP experience. You'll work with cutting-edge ML projects, automating ML pipelines, and ensuring system reliability. The role offers hybrid work options in Hyderabad or Chennai, India. We provide a competitive compensation package and emphasize professional growth. The ideal candidate brings 3+ years of MLOps experience, strong Python skills, and deep knowledge of cloud platforms. You'll be instrumental in scaling our ML operations, collaborating with data scientists, and implementing best practices in model deployment and monitoring. We foster an inclusive environment and value diverse perspectives in our team. This opportunity allows you to impact business outcomes through ML innovation while advancing your career in a rapidly evolving field.
Responsibilities For MLOps Engineer
- Design, develop, and maintain scalable and reliable MLOps pipelines on GCP
- Automate the deployment and monitoring of machine learning models in production
- Collaborate with data scientists to productionize their models and experiments
- Implement CI/CD pipelines for machine learning models
- Monitor model performance and identify areas for improvement
- Troubleshoot and resolve issues related to ML infrastructure and deployments
- Optimize ML pipelines for performance and cost efficiency
- Develop and maintain documentation for MLOps processes and infrastructure
- Stay up-to-date with the latest MLOps tools and techniques
- Ensure compliance with security and data privacy regulations
Requirements For MLOps Engineer
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- 3+ years of experience in MLOps or a related role
- Strong proficiency in Python and PySpark
- Extensive experience with Google Cloud Platform (GCP) services, including BigQuery, Airflow, and Dataproc
- Experience with containerization technologies such as Docker and Kubernetes
- Experience with CI/CD pipelines and automation tools
- Solid understanding of machine learning concepts and algorithms
- Experience with model monitoring and alerting tools
- Excellent problem-solving and communication skills
- Ability to work independently and as part of a team
- Experience with infrastructure-as-code tools such as Terraform or CloudFormation is a plus
Benefits For MLOps Engineer
- Competitive salary
- Health insurance
- Paid time off
- Professional development opportunities
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