Job title: Senior Machine Learning Engineer
Company: Arbisoft
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).
- Develop robust and scalable RAG pipelines. Integrate 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
RequirementsRequired 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.
Expected salary:
Location: Lahore, Punjab
Job date: Thu, 17 Jul 2025 22:29:24 GMT
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