Job Description
We are seeking a visionary Senior AI/ML Engineer to architect the next generation of autonomous agents. As we look toward the 2026 horizon, our mission is to build intelligent systems that not only understand language but reason, plan, and execute complex tasks with human-like proficiency.
In this role, you will be at the forefront of the Generative AI revolution, working on projects that redefine productivity and automation.
Key Responsibilities:
- Design and implement scalable architectures for Autonomous AI Agents and multi-agent systems.
- Optimize Large Language Models (LLMs) for production-grade inference, latency, and cost efficiency.
- Research and integrate cutting-edge techniques in Reinforcement Learning from Human Feedback (RLHF) and Chain-of-Thought reasoning.
- Build robust MLOps pipelines to ensure model reliability and continuous learning.
- Collaborate with product managers and designers to translate advanced AI concepts into user-friendly applications.
Qualifications:
- Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- 5+ years of professional experience in Machine Learning, Deep Learning, or NLP.
- Expert proficiency in Python, PyTorch, or TensorFlow.
- Proven track record of deploying machine learning models to high-scale production environments.
- Strong understanding of LLM fine-tuning, RAG (Retrieval-Augmented Generation), and vector databases.
Responsibilities
- Design and implement scalable architectures for Autonomous AI Agents and multi-agent systems.
- Optimize Large Language Models (LLMs) for production-grade inference, latency, and cost efficiency.
- Research and integrate cutting-edge techniques in Reinforcement Learning from Human Feedback (RLHF) and Chain-of-Thought reasoning.
- Build robust MLOps pipelines to ensure model reliability and continuous learning.
- Collaborate with product managers and designers to translate advanced AI concepts into user-friendly applications.
Qualifications
- Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- 5+ years of professional experience in Machine Learning, Deep Learning, or NLP.
- Expert proficiency in Python, PyTorch, or TensorFlow.
- Proven track record of deploying machine learning models to high-scale production environments.
- Strong understanding of LLM fine-tuning, RAG (Retrieval-Augmented Generation), and vector databases.