Machine Learning Engineer - Agentic AI & Reinforcement Learning
Viridien Group (company site, opens in a new tab)On-siteDirect career pageEst. 12–28 LPA
Posted 12h ago
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Job description
Structured overview of role & requirements
About This Role
- Design and develop single-agent and multi-agent AI systems incorporating reasoning, planning, memory, and collaboration capabilities.
- Integrate large language models, vision-language models, retrieval systems, and domain-specific tools to create robust scientific AI applications.
- Develop training environments, reward functions, evaluation metrics, and reliability guardrails; turn prototypes into reusable APIs and software components.
Minimum Requirements
- Degree in computer science, artificial intelligence, machine learning, engineering, or related discipline, or equivalent practical experience.
- Proficient in Python programming and familiar with software engineering practices.
- Experience building machine-learning, generative AI, or LLM applications through employment, internships, research, or significant academic projects.
- Experience with PyTorch, JAX, TensorFlow, or similar frameworks, and understanding of reinforcement learning, preference optimization, or sequential decision-making.
Ideal Candidate Profile
- Experience working with agentic AI concepts such as tool calling, planning, memory, and workflow orchestration, with ability to evaluate machine learning models.
- Exposure to multi-agent systems and advanced LLM fine-tuning or reinforcement-learning techniques (e.g., DPO, RLHF).
- Background or interest in applying AI to scientific, engineering, energy, or geoscience workflows in a high-performance computing environment.