Growexx is looking for smart and passionate ML-Ops Engineer, who will play a critical role in designing, implementing, and maintaining the infrastructure and tools necessary for efficient machine learning (ML) operations.
Key Responsibilities:
- Design and implement cloud solutions, build ML-Ops on AWS cloud.
- Review cloud-based ML frameworks & models, run the code refactoring & optimization for scale, containerization, deployment, versioning, model monitoring and resource management.
- Data science models testing, validation and tests automation in cloud
- ML workflow load testing for real-case requests and responses and set up a scalable solution for an ML workflow.
- Build continuous development and deployment pipelines orchestration.
- Set up a model & data quality monitoring and send alerts to stakeholders when model performances are drifted.
- Touch code at every level – from the UI, backend microservices, database, big data processing, operations, to CD/CI automation.
- Collaborate closely with data science teams to define requirements, discuss solutions, and develop high quality deliverables for our customers.
- Take ownership for the quality of the code.
Key Skills:
- Hands-on expertise with AWS Cloud Platform.
- In-depth knowledge of AWS services, including but not limited to EC2, S3, RDS, Lambda, IAM, VPC, and CloudWatch.
- Experience in creating effective CI/CD pipelines.
- Familiarity with containerization and orchestration tools, such as Docker and Kubernetes.
- Proficient in scripting and programming languages such as Python, Bash, or PowerShell.
- Experience with version control systems (e.g., Git).
- Excellent troubleshooting skills.
- Familiarity with managing ML Ops platforms.
- Understanding of machine learning concepts and practices, including model retraining, deployment, and monitoring.
Education and Experience:
- Bachelor’s or Master’s degree in computer science, Data Science, Engineering, or a related field.
- 5+ years of proven experience in creating CI/CD pipelines and working with AWS Cloud.
- Understanding of machine learning concepts and ML-Ops.
Analytical and Personal skills:
- Must have good logical reasoning and analytical skills
- Good Communication skills in English – both written and verbal
- Demonstrate Ownership and Accountability of their work
- Attention to details
