Qureos Mentor

Arbisoft

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 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:
 
 
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 Design, implement, and evaluate ML/DL models using PyTorch, TensorFlow, or similar frameworks
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 Build and optimize LLM-based systems, including prompt-tuning, fine-tuning, and adapter-based training (e.g., LoRA, QLoRA)
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 Develop robust and scalable RAG pipelines. Integrate vector databases like FAISS, Pinecone, Weaviate, etc.
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 Construct and maintain Agentic AI workflows involving multi-step reasoning, tool calling, memory components, and planning logic.
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 Work with Proprietary APIs, as well as open-source libraries and models.
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 Develop modular and clean Python code, adhering to software engineering best practices (OOP, reusable components, testing).
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 Implement scalable solutions in cloud environments (like AWS), leveraging GPU/TPU resources effectively.
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 Design inference pipelines that are robust and optimized for latency and throughput.
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 Collaborate with research and product teams to translate ideas into production-grade ML features.
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 Required Skills:
 
 
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 3+ years of experience in machine learning and deep learning, including building models from scratch.
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 Has a track record of shipping ML solutions that scale in production.
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 Strong proficiency in Python and deep understanding of software design principles.
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 Proven experience with transformer-based architectures, LLMs, and embedding models.
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 Hands-on experience with RAG systems, deep understanding of agent-based systems.
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 Familiarity with LangChain, LlamaIndex, or similar frameworks.
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 Experience with cloud platforms (AWS/GCP/Azure) and understanding of scalability, resource optimization, and model deployment.
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 Familiarity with performance profiling, efficient model serving, and hardware-aware design (e.g., GPU utilization, quantization).
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 Ability to read, debug, and contribute to complex ML/DL codebases.
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 Good to have:
 
 
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 Experience with MLOps, orchestration tools (e.g., Airflow, AWS Step Functions), containerization (Docker, Kubernetes.
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 Exposure to optimization toolkits (ONNX, TensorRT) and serving frameworks (Triton, TorchServe).
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 Experience with experiment tracking (e.g., Weights &amp; Biases, Comet)
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 Understanding of alignment techniques like RLHF or curriculum learning
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Senior ML Engineer – LLMs and RAG Systems

Join Arbisoft and explore 1   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Arbisoft

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Senior ML Engineer – LLMs and RAG Systems