Senior ML Engineer Arbisoft

Lahore - Pakistan

Monthly Salary: Not Disclosed

Posted on: 2 days ago

Vacancies: 1 Vacancy

Job Summary

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 -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.

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 ...

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

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 -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.