AI/ML Engineer

iSystems Ltd; Punjab; On-site; PKR 2,000,000 - 3,500,000; Full time

Job summary

iSystems Ltd is seeking an AI/ML Engineer with hands-on GenAI experience to design, build and ship production-grade ML apps. You will work on classical models, RAG pipelines, and multi-agent orchestration, ensuring reliability in production.

The role requires strong Python skills, cloud AI service knowledge, and a track record shipping production systems with measurable business impact. Collaboration with clients and teams is essential.

Qualifications

• 5–7 years of AI/ML engineering experience with strong GenAI hands-on.
• Second bullet not trimmed

Responsibilities

• Apply core ML techniques to business problems: framing the problem, preparing data and features, and training, tuning and validating models.
• Design, build and deploy multiple production-grade GenAI applications in Python using agentic frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen or CrewAI.
• Own the GenAI lifecycle: prompt engineering, RAG pipeline design, LLM evaluation and fine-tuning.
• Architect multi-agent systems covering supervisor and parallel patterns, human-in-the-loop steps and agent memory.
• Implement production safeguards, including guardrails, content moderation, and mitigation of prompt injection and data leakage.
• Deploy and monitor models and LLM applications in production, with attention to drift, quality and cost.
• Apply sound software engineering practice: system design, API development, testing and CI/CD.
• Build on loud AI services (Azure OpenAI, AWS Bedrock or GCP Vertex AI) and vector databases
• Define and track evaluation metrics so that business impact and quality can be demonstrated and improved over time.
• Collaborate with engineers, project leads and client stakeholders and contribute to design reviews and technical documentation.

Skills

Python

GenAI experience

AI/ML engineering

Cloud AI services

LLM evaluation

CI/CD

communication

multi-agent orchestration

data preparation

problem framing

Tools

LangGraph

LangChain

Semantic Kernel

AutoGen

CrewAI

PyTorch

TensorFlow

scikit-learn

Pinecone

Weaviate

pgvector

Job description

We are hiring an AI/ML Engineer who combines core machine learning expertise with hands-on Generative AI experience. You will design, build and ship production-grade ML and GenAI applications with measurable business impact, from classical model development and evaluation to RAG pipelines and multi-agent orchestration, and apply the safeguards that keep these systems reliable in production. This role is for someone who has taken models beyond proof of concept.

Key Responsibilities

• Apply core ML techniques to business problems: framing the problem, preparing data and features, and training, tuning and validating models.
• Design, build and deploy multiple production-grade GenAI applications in Python using agentic frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen or CrewAI.
• Own the GenAI lifecycle: prompt engineering, RAG pipeline design, LLM evaluation and fine-tuning.
• Architect multi-agent systems covering supervisor and parallel patterns, human-in-the-loop steps and agent memory.
• Implement production safeguards, including guardrails, content moderation, and mitigation of prompt injection and data leakage.
• Deploy and monitor models and LLM applications in production, with attention to drift, quality and cost.
• Apply sound software engineering practice: system design, API development, testing and CI/CD.
• Build on loud AI services (Azure OpenAI, AWS Bedrock or GCP Vertex AI) and vector databases
• Define and track evaluation metrics so that business impact and quality can be demonstrated and improved over time.
• Collaborate with engineers, project leads and client stakeholders and contribute to design reviews and technical documentation.

Required Qualifications

• 5–7 years of experience in AI/ML engineering, with strong core ML expertise and hands-on GenAI experience.
• Strong foundation in machine learning: supervised and unsupervised learning, statistics, feature engineering, model training, evaluation and tuning, using frameworks such as scikit-learn, PyTorch or TensorFlow.
• Proven experience building and shipping multiple production-grade ML and GenAI applications (not just POCs) with demonstrable business impact.
• Strong Python skills and hands-on experience with agentic frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen or CrewAI.
• Hands-on experience across the GenAI lifecycle: prompt engineering, RAG pipeline design, LLM evaluation and fine-tuning.
• Experience with multi-agent orchestration (supervisor, parallel, human-in-the-loop, agent memory).
• Experience applying production safeguards: guardrails, content moderation, and mitigation of prompt injection and data leakage.
• Strong software engineering fundamentals: system design, APIs and CI/CD.
• Working knowledge of at least one cloud AI service (Azure OpenAI, AWS Bedrock or GCP Vertex AI) and one vector database (Pinecone, Weaviate or pgvector).
• Strong Communication skills as you will be working directly with the client

Preferred Qualifications

• Experience with Databricks.
• Experience with LLM MLOps tooling.
• Experience building AI for BI solutions using databricks