Applied ML Engineer
Description For Applied ML Engineer
Kognitos is pioneering the future of software development through cutting-edge multi-agent automation platforms in the trillion-dollar hyper-automation market. As an Applied ML Engineer, you'll be at the forefront of developing innovative solutions for agentic workflows and enterprise automation.
You'll work on crucial projects including efficient fine-tuning of models, developing agentic workflows for reliable AI task execution, and creating multimodal language models for enterprise applications. The role involves optimizing AI systems that can significantly reduce operational expenses through large-scale adoption.
The ideal candidate brings strong expertise in machine learning, with experience in model deployment and fine-tuning. You'll be working with state-of-the-art AI technologies, including LLMs and multimodal models, while ensuring solutions align with enterprise needs and regulatory requirements.
Join a world-class team of engineers and researchers working on transformational changes in enterprise operations. You'll have the opportunity to tackle some of AI's hardest problems while contributing to a platform that's revolutionizing how software is built and maintained.
This role offers competitive compensation ($200K-$240K with equity) and the chance to work at the company's headquarters in the San Francisco Bay Area. Kognitos values diversity and maintains an inclusive work environment, welcoming candidates from all backgrounds to apply even if they don't meet all listed qualifications.
Responsibilities For Applied ML Engineer
- 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
- Stay at the cutting edge of AI research, incorporating new advancements into Kognitos' platform
Requirements For Applied ML Engineer
- 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
- Familiarity with multimodal language models and their enterprise applications
- Proficiency in Python, TensorFlow, PyTorch, or similar frameworks
- Excellent problem-solving skills and ability to work in a fast-paced environment
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