Data Scientist and LLM Engineer

abra R&D is seeking an experienced Algorithm and Signal Processing Engineer

We are seeking a Data Scientist and LLM Engineer with a strong background in Python and hands-on experience in developing and implementing advanced ML and NLP solutions.

• The ideal candidate will bring in-depth technical skills and industry experience to design, develop, and optimize AI/ML models, particularly Large Language Models (LLMs), to address complex challenges in our target sectors ementation in simulation environments.
• Support software, hardware, and firmware teams in implementing algorithms on embedded systems.

Responsibilities

• Design, develop, and deploy cutting-edge causal inference and AI models to solve complex problems in user behavior, root cause analysis, gaming and mobile applications domains.
• Develop Python-based solutions for data processing, model training, and deployment in production environments.
• Collaborate with cross-functional teams to integrate AI/ML solutions into enterprise-grade applications.
• Conduct research on the latest advancements in AI, ML, and LLMs to maintain competitive edge.
• Optimize and fine-tune LLMs for performance, scalability, and cost efficiency.
• Analyze and process large datasets to extract actionable insights that drive business value.
• Develop and maintain robust, scalable, and efficient codebases and documentation.

Why Join Us

• Be part of a forward-thinking start-up company pushing the boundaries of AI and ML.
• Collaborate with a talented team dedicated to innovation and excellence.
• Opportunities for professional growth and development in cutting-edge technologies.

Must-Have Requirements:

• Master’s or Ph.D. in Computer Science, Electrical Engineering, Mathematics, or a related field.
• 4 + years of professional Python development, designing and implementing end-to-end machine-learning pipelines.
• ⁠Practical experience with Generative AI techniques,
• Proven hands-on experience with Large Language Models (LLMs) and Transformer architectures.
• Extensive hands-on experience with NLP frameworks and libraries, such as Hugging Face Transformers, PyTorch, and OpenAI APIs.
• Proven ability to deploy AI/ML models to production, with a focus on scalability and robustness
• Excellent understanding of unstructured and semi-structured data processing methods.

Advantageous Qualifications (Nice to Have)

• Experience working in cloud environments (AWS, GCP, or Azure) and leveraging distributed computing frameworks (e.g., Spark or Ray).