MLOps Engineer
- Industry Other
- Category Production/Maintenance /Quality
- Location Kathmandu, Nepal
- Expiry date Mar 15, 2026 (4 days left)
Job Description
About Vertex Special TechnologyVertex Special Technologies is a leading digital innovation company in Nepal, dedicated to transforming business processes through cutting-edge technology. Established with a vision to deliver world-class full-stack software solutions—from startups to Fortune 500 enterprises—we combine IT consultancy excellence with robust product engineering. With a growing global presence across the USA, Nepal, Pakistan, the UK, and Dubai, we empower organizations to achieve operational excellence and accelerate revenue growth through modern, scalable, and impactful tech solutions..
About The Role
We are looking for an MLOps Engineer to build and optimize ML pipelines, productionize ML/LLM models, manage cloud-based ML infrastructure, and ensure smooth deployment, monitoring, and automation. The role involves implementing CI/CD for ML, maintaining model and data health, and defining best practices for scalable and reliable ML operations.
- Build, manage and scale workflows and MLOPs pipelines for model deployment, monitoring and automation.
- Partner with data scientists and machine learning engineers to productionize ML and LLM models (including retrieval-augmented generation or similar architectures) and across environments (dev, staging, prod)
- Implement CI/CD for ML (CI/CD for code, data, and models), including automated tests, model validation, and secure artifact promotion.
- Monitor model and data health in production (performance, drift, data quality, latency, cost), and define SLOs/alerts with observability tools (e.g., Prometheus, Grafana, OpenTelemetry).
- Manage ML infrastructure on cloud platforms (AWS, GCP, or Azure), including containers (Docker), orchestration (Kubernetes), and job schedulers (Airflow, Argo, etc.)
- Optimize Python based components for performance.
- Optimize infrastructure to support high-performance model execution and scalable experimentation.
- Define standards, best practices, and reusable components for the MLOps lifecycle and Create and maintain documentation for ML workflows, runbooks, and operational playbooks.
- Ensure compliance with data privacy, responsible AI, and governance requirements.
Education: Bachelor's degree or above in Computer Science, Software Engineering, or a related field.
Experience: At least 1+ years (junior) / 3+ years (MID) years experience proven experience in both Machine Learning and python programming.
What We Offer
- An attractive and competitive compensation package
- A dynamic engineering culture built on collaboration, agility, and continuous innovation.
- Ample opportunities to grow your technical expertise and accelerate your career path.
- Hands-on experience working on global projects and enterprise-scale platforms.
- Comprehensive benefits including medical coverage, paid leaves, and additional employee perks.
- A meaningful role where your work directly contributes to impactful, customer-driven solutions.
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