Senior ML Engineer Infrastructure & Data Systems - Arbisoft
Taraki
Date: 2 weeks ago
City: Lahore
Contract type: Full time
Our client Arbisoft is hiring a Senior ML Engineer Infrastructure & Data Systems in Lahore.
What you'll be doing
- Building and maintaining CI/CD pipelines using GitHub Actions
- Designing and managing deployment configurations for Docker Swarm and Kubernetes,
- evaluate ML/DL models using PyTorch, TensorFlow, or similar frameworks.
- Build and optimize LLM-based systems, including prompt-tuning, fine-tuning, and adapter-based training (e.g., LoRA, QLoRA).
- Owning infrastructure automation and applying solid DevOps practices across environments
- Setting up and maintaining monitoring for services running in production
- Writing automated tests and building testing frameworks that scale with the codebase
- Troubleshooting and maintaining complex, sometimes messy codebases and improving them
- Actively identifying and resolving technical debt
- Working with SQL and handling data processing tasks as needed
- Occasionally training simple ML models (e.g. regression models in PyTorch)
- Can develop robust and scalable RAG pipelines. In-depth knowledge of embeddings and can work with vector databases like FAISS, Pinecone, Weaviate, etc.
- Communicating clearly and consistently with engineers, data scientists, product managers, and business stakeholders
- 5 years of industry experience building and shipping software
- BS in Computer Science or masters
- Strong command of CI/CD workflows, GitHub Actions, Docker, and infrastructure automation
- Solid experience with Kubernetes and Docker Swarm deployment setups
- Good working knowledge of SQL and data processing
- Strong code engineering fundamentals, can read, debug, and maintain codebases you didn't write
- A track record of dealing with tech debt, not just avoiding it
- Excellent communication skills who can explain technical tradeoffs to non-technical stakeholders and stay aligned with cross-functional teams over time
Once a task is assigned, you're expected to own it end-to-end:
- Understand the task fully and clarify uncertainties upfront
- Create and maintain a clear ticket, aligned with the team on scope
- Set an estimate once scoped
- Flag blockers early and communicate delays as soon as they arise
- Let the team know if you finish early
- Share at least a weekly update, more often when there are significant changes
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