Junior Research And Development Engineer

We are seeking a Research Engineer to join our cutting-edge research team focused on developing state-of-the-art machine learning models, including Large Language Models (LLMs), Agentic Systems, and Retrieval-Augmented Generation (RAG). In this role, you will contribute to innovative AI research, develop novel algorithms, and push the boundaries of autonomous systems, all while working in a collaborative and dynamic environment.

Key Responsibilities:

• Conduct research in machine learning, LLMs, agentic systems, and RAG to contribute to state-of-the-art solutions in AI.
• Design, implement, and optimize LLMs and agentic systems, focusing on tasks involving reasoning, decision-making, and autonomous behaviour.
• Develop testing methodologies and evaluate the performance of AI models using real-world benchmarks.
• Leverage external knowledge bases through RAG to improve model results and create more accurate, context-aware systems.
• Focus on scalable deployment of AI models, ensuring efficiency in computing resource usage and system reliability.
• Explore novel algorithms and techniques that advance the capabilities of AI systems.

Required Skills & Qualifications:

Experience:

• 1+ years of experience in machine learning or AI research, with a strong focus on NLP and deep learning.
• Proven track record in the development and optimization of Large Language Models (LLMs) and agentic systems.
• Experience with Retrieval-Augmented Generation (RAG) models and using external knowledge to improve generative models.

Technical Skills:

• Proficiency in Python, TensorFlow, PyTorch, and other popular machine learning frameworks.
• Strong understanding of transformer architectures (e.g., GPT, BERT) and their application to NLP tasks.
• Experience in reinforcement learning, multi-agent systems, and decision-making models is highly desirable.
• Familiarity with large-scale data processing and cloud platforms (e.g., AWS, GCP, Azure).
• Experience with model deployment and optimization for scalability in real-world environments.

Additional Skills:

• Familiarity with knowledge graphs, semantic search, or information retrieval systems.
• Ability to clearly communicate complex technical concepts to both technical and non-technical stakeholders.
• Strong analytical and problem-solving skills with a focus on innovative thinking.

Desired Attributes:

• Passion for advancing AI and machine learning technologies, particularly in the fields of NLP and autonomous systems.
• Collaborative mindset, with the ability to work effectively in cross-disciplinary teams.
• Self-motivated, with a strong drive for continuous learning and research.
• Ability to think critically and creatively to solve complex, open-ended problems.