AI based research and ICT solution. Next Solution Lab is a family of well-organized Software Engineers, Researchers and Specialists with diverse experiences collaborating to solve your next innovation challenges. We research and develop state-of-the-art technology to support digital transformation and system development needs.
Number of Position
:
1
Employment Type
:
Full Time
Job Location
:
Dhaka (DOHS Mirpur)
Educational Requirement
:
Bachelor of Science (BSc) in Computer Science & Engineering, Master of Science (MSc) in Computer Science & Engineering
Other Requirement
:
Experience:
Minimum of 2 years of hands-on experience in MLOps or DevOps with a focus on machine learning systems.
Technical Skills:
Proficiency in AWS cloud services (EC2, S3, Lambda, etc.).
Strong experience in automating ML pipelines using tools like MLflow, Kubeflow, or similar.
Experience with containerization (Docker) and orchestration (Kubernetes).
Expertise in scripting languages (Python, Bash, etc.) and configuration management tools.
System Architecture:
Proven ability to design, implement, and maintain scalable, high-performance system architectures for ML applications.
Collaboration:
Excellent communication skills and the ability to work effectively in a cross-functional, fast-paced environment.
Experience
:
At least 2 years
Responsibilities
:
Next Solution Lab is a pioneering AI research and software development company dedicated to delivering cutting-edge solutions. We are committed to innovation and excellence, driving digital transformation through advanced AI and cloud technologies.Job Description:We are seeking a skilled and proactive DevOps Engineer with a strong focus on MLOps to join our dynamic team. The ideal candidate will have hands-on experience in automating machine learning workflows, managing scalable cloud infrastructures (especially AWS), and designing robust system architectures. You will collaborate with data scientists, ML engineers, and software developers to deploy and maintain production-level ML pipelines.Responsibilities:
ML Pipeline Automation: Design, build, and maintain automated ML pipelines for training, validation, deployment, and monitoring of machine learning models.
Cloud Infrastructure & AWS Management: Architect, deploy, and manage scalable and secure AWS cloud environments (EC2, S3, Lambda, ECS/EKS, etc.) to support ML workloads and DevOps practices.
Continuous Integration/Continuous Deployment (CI/CD): Implement and optimize CI/CD pipelines specifically tailored for ML workflows, integrating code testing, model validation, and automated deployments.
System Architecture & Automation: Develop and maintain robust system architectures to support high-performance ML systems, ensuring reliability, scalability, and efficient resource utilization.
Monitoring & Logging: Establish monitoring and logging solutions for deployed models and infrastructure, ensuring real-time performance tracking and prompt issue resolution.
Collaboration & Best Practices: Work closely with cross-functional teams to integrate DevOps best practices into ML lifecycle management. Contribute to the development of technical documentation, guidelines, and process improvements.
Security & Compliance: Ensure security best practices in cloud configurations, data access, and deployment processes, adhering to industry standards and compliance requirements.
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