
AI/ML Software Engineer @ Antal
14 hours ago
What You Bring:
- Strong grasp of LLM architecture, prompt engineering, and RAG fundamentals
- Hands-on experience fine-tuning pre-trained models for domain adaptation
- Solid foundation in machine learning, deep learning, and NLP techniques
- Proficiency in Python and SQL, and familiarity with CI/CD development pipelines
- Knowledge of cloud environments such as Azure or GCP
- A collaborative mindset and the ability to present technical ideas with clarity
- Passion for building ethical, inclusive, and human-centered AI
B2B | hybrid (6-8 times per month)
Are you passionate about artificial intelligence and ready to turn cutting-edge research into real-world applications? Join our dynamic AI team as a Software Engineer, where you’ll help build powerful, responsible, and scalable solutions using Large Language Models and the latest in machine learning.
We’re looking for someone who thrives on innovation, understands the landscape of LLMs, and enjoys developing systems that combine deep technical skill with business impact. You’ll be working at the intersection of AI and real-world problem-solving—designing prompts, fine-tuning models, and deploying intelligent tools that make a difference.
This is your chance to work on high-impact AI systems in a team that values creativity, ownership, and continuous learning. If you're ready to bring intelligent solutions to life—apply today
,[Design and test effective prompts for LLMs across diverse use cases, Fine-tune large-scale pre-trained models using domain-specific data, Build and integrate Retrieval-Augmented Generation (RAG) pipelines, Work with vector databases and optimize NLP systems for speed and accuracy, Collaborate with cross-functional teams to align AI development with business goals, Ensure fairness, transparency, and accountability in AI models and workflows, Develop and maintain code using Python, SQL, GitHub, and CI/CD tools, Deploy AI models using cloud platforms like Azure or GCP, Communicate technical concepts clearly to both tech and non-tech stakeholders] Requirements: Machine learning, Deep learning, NLP, Python, SQL, Cloud, Azure, GCP, AI-
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