Applied ML Engineer

Responsibilities

• Design, implement, and deploy machine learning models focused on agentic workflows and deterministic task execution.
• Optimize AI systems for multimodal applications, addressing real-world enterprise challenges.
• Innovate on fine-tuning techniques to maximize resource efficiency and improve model performance.
• Ensure AI systems are aligned to regulatory policies and deliver consistent business value.
• Collaborate with cross-functional teams, including product, engineering, and business stakeholders, to deliver impactful solutions.
• Stay at the cutting edge of AI research, incorporating new advancements into Kognitos’ platform.

Requirements

• Bachelor’s, Master’s, or Ph.D. in Computer Science, Machine Learning, or a related field.
• Proven experience in developing and deploying machine learning models in production environments.
• Expertise in fine-tuning techniques for large-scale models and optimizing resource usage.
• Strong intuition working with LLMs.
• Proficiency in Python, TensorFlow, PyTorch, or similar frameworks.
• Excellent problem-solving skills and the ability to work in a fast-paced, dynamic environment.

Preferred Qualifications

• Experience with agentic workflows and multi-agent systems.
• Knowledge of enterprise automation challenges and opportunities.
• Prior work in AI for non-consumer use cases, especially in large-scale enterprise environments.
• Familiarity with cloud platforms and distributed computing frameworks.