Job Description
We are seeking a visionary Senior AI/LLM Engineer to lead the development of our next-generation Autonomous AI Agents. As we look toward the 2026 paradigm shift in artificial intelligence, our mission is to build systems that don't just process language but truly understand context, intent, and multi-modal reasoning.
In this role, you will be at the forefront of defining what 'intelligence' looks like in the next era. You will architect scalable solutions, fine-tune foundation models, and deploy intelligent agents capable of complex decision-making. If you are passionate about the future of AGI and want to build the infrastructure for tomorrow, we want to hear from you.
Responsibilities
- Architect & Deploy: Design and implement robust, high-performance AI architectures for autonomous agents using Python, PyTorch, and distributed systems.
- Model Fine-Tuning: Optimize large language models (LLMs) for specific enterprise use cases, improving accuracy, safety, and reduction of hallucinations.
- RAG & Vector Databases: Engineer advanced Retrieval-Augmented Generation pipelines to ensure agents have access to real-time, accurate knowledge bases.
- MLOps Implementation: Build CI/CD pipelines for machine learning, ensuring models are versioned, monitored, and retrained efficiently.
- Multi-Modal Integration: Work on integrating vision and audio capabilities into the AI framework to create truly multimodal agents.
- Ethical AI: Establish guardrails and safety protocols to ensure AI outputs align with ethical standards and regulatory requirements.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field.
- Experience: 5+ years of experience in machine learning, deep learning, or NLP. Proven track record of shipping production-level AI models.
- Technical Skills: Strong proficiency in Python, PyTorch, TensorFlow, or JAX. Experience with Hugging Face Transformers and LangChain.
- Infrastructure: Experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker/Kubernetes).
- Problem Solving: Ability to debug complex distributed systems and optimize model inference latency.
- Communication: Excellent verbal and written skills to translate technical concepts to non-technical stakeholders.