Qureos

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AI Engineer / AI Research Scientist / Applied Scientist

India

Job Title: AI Engineer / AI Research Scientist / Applied Scientist
Location: 100% Remote (India)
Duration: 12-Month Contract

About the Role

We are seeking a highly skilled and motivated AI Engineer to design, develop, and deploy cutting-edge AI/ML solutions in production-grade environments. This role requires a blend of strong software engineering expertise, deep knowledge of AI/ML frameworks, and hands-on experience in agentic AI, large-scale distributed systems, and model lifecycle management. The ideal candidate will be passionate about building intelligent systems that solve complex problems across industries.

Key Responsibilities

  • Design, develop, and deploy AI/ML solutions with a focus on production scalability and performance.

  • Build, fine-tune, and optimize models in domains such as LLMs, computer vision, signal processing, generative AI, autonomous agents, and recommendation systems.

  • Work with agentic AI, AI reasoning, Digital Twins, and prescriptive AI for real-world applications.

  • Architect large-scale AI solutions leveraging APIs, microservices, and model versioning systems.

  • Implement distributed training, hyperparameter optimization, and model evaluation frameworks.

  • Integrate AI solutions with big data pipelines (Spark, Kafka, Redis, Elasticsearch) and cloud-native environments (AWS, Azure, GCP).

  • Develop high-performance AI workflows using GPUs (CUDA, Rapids, NeMo, NIM) and containerized systems (Docker, Kubernetes, Helm).

  • Apply Graph Theory and Knowledge Graph architectures (Neo4j, cuGraph) in AI system design.

  • Collaborate with cross-functional teams to deliver AI-powered solutions while ensuring explainability, fairness, and compliance.

  • Stay up to date with emerging AI technologies, frameworks, and research to drive innovation.

Required Qualifications

  • PhD in Computer Science, Applied Mathematics, or related field (with AI/deep learning/intelligent systems specialization preferred).

  • 3–5 years of experience in building and deploying AI solutions.

  • 2–3 years of experience in one or more domains: LLMs, computer vision, signal processing, generative AI, optimization, recommendation systems, or autonomous agents.

  • 1+ year of hands-on experience in agentic AI, AI reasoning, or prescriptive/decision AI.

  • 4+ years of experience in designing and deploying AI solutions in production environments.

  • Strong programming experience in Python, C/C++, PySpark, or Java/Scala.

  • Hands-on experience with DL/ML frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, LangGraph, OpenCV).

  • Experience with GPU-accelerated computing (CUDA, Rapids, NeMo, NIM).

  • Proficiency in cloud-native AI platforms (AWS, Azure, GCP) and AIOps tooling.

  • Experience in automated workflows (GitHub Actions, Terraform, Helm) and containerization (Docker, Kubernetes).

  • Strong knowledge of model architectures (LLMs, RAG, MoE, DRL, foundation models).

  • Effective communication skills with ability to engage both technical and non-technical audiences.

Preferred Skills

  • Experience in regulated industries such as finance, healthcare, or insurance.

  • Solid understanding of deep learning architectures (CNNs, RNNs, Transformers, GANs).

  • Expertise in neural networks, transformers, diffusion models, generative modeling, Bayesian inference, RL, BERT/CLIP.

  • Background in responsible AI/ML, model interpretability, and fairness auditing.

  • Proven track record of delivering large-scale, real-time AI/ML/GenAI/Agentic AI solutions.

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