AI/ML Engineer – Intelligent Systems & AI Infrastructure

About the Job

Digital Auxilius is seeking a highly skilled AI/ML Engineer to lead the development of our next-generation intelligent systems. Based in Karachi, Sindh, Pakistan, this Full-Time role offers an On-site work model designed for an Experienced (3+ years) professional who is ready to bridge the gap between experimental AI research and production-grade software. You will be responsible for architecting the AI infrastructure and multi-agent systems that automate complex workflows and process unstructured data at scale, serving as a core driver of our platform's backend intelligence.

Role Overview

As an AI/ML Engineer, you aren't just building models; you are designing the intelligent backbone of our infrastructure. Your work will focus on creating autonomous systems that coordinate tools, APIs, and data sources to solve real-world operational challenges at the forefront of the generative AI shift.

Key Responsibilities

1. AI/ML System Development & Architecture

• Agentic Systems: Design and implement multi-agent architectures that coordinate tools, APIs, and data sources to perform complex, autonomous tasks.
• Conversational AI: Develop voice and text-based agents capable of real-time interaction using speech recognition and advanced dialogue orchestration.
• RAG Pipelines: Build and optimize Retrieval-Augmented Generation (RAG) pipelines, combining vector databases with large-scale knowledge sources.
• Infrastructure: Architect scalable backend microservices and optimize inference pipelines for low latency and cost-efficiency.

2. Data Engineering & MLOps

• Pipeline Management: Design automated ingestion pipelines to process and transform structured and unstructured datasets for model training.
• Lifecycle Management: Implement model versioning, experiment tracking (using tools like MLflow or W&B), and CI/CD pipelines specifically for ML systems.
• Monitoring: Establish robust observability to monitor deployed models for data drift and performance degradation.

3. Quality, Security & Governance

• Evaluation Frameworks: Create structured testing environments to measure system performance and mitigate risks such as hallucinations.
• AI Safety: Build safeguards to ensure secure handling of sensitive data and prevent unintended system outputs.

Technical Requirements

• Education: Bachelor's or Master's in Computer Science, Artificial Intelligence, or a related field.
• Core Programming: Mastery of Python and experience building production-grade backend services.
• Frameworks: Deep expertise in PyTorch, HuggingFace Transformers, and LangChain.
• Data Systems: Practical knowledge of vector databases (Pinecone, Weaviate, or FAISS) and high-dimensional indexing.
• Integrations: Proven ability to build integrations between internal databases and third-party AI platforms via REST APIs.

Preferred Qualifications

• Experience deploying AI services using Docker, Kubernetes, and cloud infrastructure (AWS, GCP, or Azure).
• Familiarity with low-code automation platforms such as n8n.
• Experience with real-time AI interaction systems or large-scale document analysis.

Why Join Us?

You will move beyond simple chatbots to create integrated, autonomous systems that solve complex operational challenges within a forward-thinking engineering culture.