Machine Learning (ML) Engineer (Senior) - Arbisoft

taraki-search; Lahore; On-site; PKR 3,500,000 - 6,000,000; Full time

Job summary

Arbisoft in Lahore seeks a Senior ML Engineer to design and deploy AI solutions, including LLMs, RAG pipelines, and agentic workflows.

The candidate should have deep Python expertise, transformer knowledge, and experience building scalable cloud-based ML systems. Collaboration with research and product teams is essential for production-grade features.

Qualifications

• 5+ years of experience in machine learning and deep learning, including building models from scratch.

Responsibilities

• Design, implement, and evaluate ML/DL models using PyTorch, TensorFlow, or similar frameworks.

Skills

Python proficiency

Transformer models

ML deployment

RAG systems

Agent-based workflows

Documentation & testing

Tools

LangChain

LlamaIndex

FAISS

Pinecone

Weaviate

Job description

Our client Arbisoft is looking for Senior ML Engineer in Lahore.

Job Description:

Arbisoft is looking for an experienced ML Engineer to design and deploy cutting-edge AI solutions, including LLMs, RAG pipelines, and agentic workflows. The ideal candidate brings deep expertise in Python, transformers, and scalable cloud-based ML systems.

Key Responsibilities:

• Design, implement, and 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).
• Can develop robust and scalable RAG pipelines. In-depth knowledge of embeddings and can work with vector databases like FAISS, Pinecone, Weaviate, etc.
• Construct and maintain Agentic AI workflows involving multi-step reasoning, tool calling, memory components, and planning logic.
• Work with Proprietary APIs, as well as open-source libraries and models
• Develop modular and clean Python code, adhering to software engineering best practices (OOP, reusable components, testing).
• Implement scalable solutions in cloud environments (like AWS), leveraging GPU/TPU resources effectively.
• Design inference pipelines that are robust and optimized for latency and throughput.
• Collaborate with research and product teams to translate ideas into production-grade ML features.

Required Skills:

• 5+ years of experience in machine learning and deep learning, including building models from scratch.
• Has a track record of shipping ML solutions that scale in production.
• Strong proficiency in Python and deep understanding of software design principles.
• Proven experience with transformer-based architectures, LLMs, and embedding models.
• Hands-on experience with RAG systems, deep understanding of agent-based systems. Familiarity with LangChain, LlamaIndex, or similar frameworks.
• Experience with cloud platforms (AWS/GCP/Azure) and understanding of scalability, resource optimization, and model deployment.
• Familiarity with performance profiling, efficient model serving, and hardware-aware design (e.g., GPU utilization, quantization).
• Ability to read, debug, and contribute to complex ML/DL codebases.

Good to have:

• Experience with MLOps, orchestration tools (e.g., Airflow, AWS Step Functions), containerization (Docker, Kubernetes).
• Exposure to optimization toolkits (ONNX, TensorRT) and serving frameworks (Triton, TorchServe).
• Experience with experiment tracking (e.g., Weights & Biases, Comet).
• Understanding of alignment techniques like RLHF or curriculum learning.