MLOps Engineer (Machine Learning)

Job Description

Title: MLOps Engineer (Machine Learning)

Company Name: Silicon Orchard Ltd.

Vacancy: 3

Age: Na

Job Location: Dhaka

Salary: Negotiable

Experience:

• At least 3 years
• The applicants should have experience in the following business area(s): Software Company

• Bachelor in Engineering (BEngg)

• Published or under-reviewed papers in reputed IEEE conferences, book chapters, or journals will be a plus.

• At least 3 years
• The applicants should have experience in the following business area(s): Software Company

• Familiarity with Large Language Models (LLMs) is an added advantage.
• Having an Associate Cloud Certification in platforms like AWS or Azure is desirable.

Silicon Orchard Limited is excited to announce that we seek talented individuals to join our machine learning team. We believe this role will provide a platform for personal and professional growth while pushing the boundaries of ML innovations. A strong focus on MLOps is essential for ensuring scalable and reliable deployment of models.

Job Responsibilities:

• Develop and maintain efficient end-to-end pipelines for AI and LLM-based applications, ensuring seamless transitions from development to production environments.
• Design, build, and maintain scalable machine learning services that support reliable data science operations.
• Implement CI/CD pipelines using orchestration tools such as GitLab CI, GitHub Actions, or similar systems to automate workflows.
• Design and implement cloud solutions (AWS, Azure, Digital Ocean) to build and optimize MLOps infrastructures on the cloud.
• Continuously monitor application performance metrics and system health, ensuring high availability, performance, and reliability of ML systems such as MLflow, Weights & Biases (W&B).
• Implement best practices for scaling and operating ML models in production environments.
• Preprocess and collect data for model training, evaluation, and deployment purposes.
• Collaborate with cross-functional teams including data scientists, data engineers, and architects to ensure seamless project delivery and maintain proper documentation.
• Stay up-to-date with emerging technologies and trends in machine learning infrastructure, distributed systems, and MLOps practices.

• Over time allowance,Weekly 2 holidays
• Salary Review: Yearly
• Lunch Facilities: Full Subsidize
• Festival Bonus: 2
• Weekly 2 holidays (Saturday & Sunday)
• Salary Review: Yearly
• Overtime allowance
• Festival Bonus: 2 (Yearly)
• Lunch & Breakfast - Full Subsidize
• Hybrid work (In-office & remote)
• Performance bonus
• Great work environment
• Facilities for skill development