Qureos Mentor

RDA Labs

<div></div><div><div><div><div><div><div><div><div><div><h4 class="jobSectionHeader"><b>Experience:</b></h4><b>
</b></div></div><div><div><ul><li>3&ndash;5 years of hands-on experience developing AI/ML algorithms and solution frameworks</li><li>
2-3 years of experience in one or more domains: language model, computer vision, signal processing, generative AI, optimization programming, recommendation systems, or autonomous agents</li><li>
1+ year of experience in agentic AI and/or AI reasoning, Digital Twins, Decision/Prescriptive AI</li><li>
3-5 years of programming in Python and C++. CUDA is a plus</li></ul>
</div></div><div><div><p><b>Skills:</b></p><b>
</b></div></div><div><div><ul><li>Strong foundation in mathematics: linear algebra, probability, stochastics, optimization theory</li><li>
Expertise in mathematical programming, algorithm design, and optimization techniques</li><li>
Skilled in formulating complex problems and designing scalable algorithms (e.g. linear/non-linear programming, convex optimization, combinatorial algorithms, etc.) and experience improving algorithms for efficiency and scalability</li><li>
Deep knowledge of machine learning, deep learning, and statistical modeling</li><li>
Strong in Graph Theory or Knowledge Graph related architecture and database (e.g. Neo4j, cuGraph)</li><li>
Hands-on experience with neural networks, transformers, diffusion models, or generative modeling</li><li>
Familiarity with NLP, computer vision, or domain-specific AI applications</li><li>
Proficient in model evaluation, validation, and performance metrics</li><li>
Experience with AI/ML frameworks and libraries (e.g. TensorFlow, PyTorch)</li><li>
Familiarity with software development practices (version control, testing, GPU accelerated computing)</li><li>
Strong analytical thinking and problem-solving skills</li><li>
Ability to derive insights and prove algorithmic effectiveness through rigorous logic and math</li><li>
Demonstrated creativity in tackling open-ended research and real-world AI challenges</li><li>
Clear communicator, able to translate complex ideas for technical and non-technical audiences</li><li>
Effective collaborator in cross-functional teams with researchers, engineers, and business partners</li><li>
Skilled in writing technical documentation, reports, and academic publications is a plus</li><li>
Passion for AI advancement and continuous learning</li><li>
Active interest in emerging AI research, with contributions to publications, open-source projects or conference preferred</li></ul>
</div></div><div><div><p><b>Preferred Skills:</b></p><b>
</b></div></div><div><div><ul><li>Experience in regulated industries (e.g., finance, healthcare, insurance)</li><li>
Excellent communication and stakeholder engagement skills</li><li>
Strong in GPU based accelerating computing technologies (CUDA, Rapids, NeMo, NIM, etc.)</li><li>
Proficiency in model evaluation, distributed training, and hyperparameter optimization</li><li>
Proficient in Big Data Theory based large scale data streaming and in-memory database technologies (Spark, Kafka, Redis, Elastic Search)</li><li>
Strong in automated workflow technologies (GitHub Actions, Terraform, Helmet) and containerization technologies (Docker, Kubernetes)</li><li>
Proficient in API, MCP and Microservices technologies</li><li>
Track records in large-scale, real-time AI/GenAI/AgenticAI/ML database and solution technologies</li><li>
Background in responsible AI/ML, model interpretability, and fairness auditing</li></ul>
</div></div><div><div><p><b>Education </b><b>:</b></p><b>
</b></div></div><div><div><ul><li>Ph.D.&rsquo;s or Master&rsquo;s in Computer Science, Applied Mathematics, Engineering, or related field with AI/Optimization focus</li><li>
Proven experience in applied AI Research with deployment of AI solutions in real-world settings</li></ul></div></div></div></div></div></div></div></div></div><div></div>

AI Research Scientist

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AI Research Scientist