Applied ML Engineer
Quick Summary
If you’re passionate about tackling some of the hardest problems in AI and contributing to transformational change in enterprise automation, join us at Kognitos to build the future of software.
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.
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.
If you’re passionate about tackling some of the hardest problems in AI and contributing to transformational change in enterprise automation, join us at Kognitos to build the future of software.
Efficient Fine-Tuning: Develop innovative methods to optimize resource usage for training and fine-tuning models, ensuring high performance while maintaining efficiency.
Agentic Workflows: Advance workflows that allow AI to reason, plan, and execute tasks with reliability and determinism, minimizing errors and runtime surprises.
Multimodal Language Models: Work on multimodal use cases, combining text, images, and other data formats, to build adaptive, enterprise-ready automation tools.
Scalable AI for Enterprises: Address the needs of enterprises by creating AI solutions that can remove 30% of operational expenses through large-scale adoption.
Responsibilities
~1 min read- →
Design, implement, and deploy machine learning models focused on agentic workflows and deterministic task execution.
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Optimize AI systems for multimodal applications, addressing real-world enterprise challenges.
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Innovate on fine-tuning techniques to maximize resource efficiency and improve model performance.
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Ensure AI systems are aligned to regulatory policies and deliver consistent business value.
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Collaborate with cross-functional teams, including product, engineering, and business stakeholders, to deliver impactful solutions.
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Stay at the cutting edge of AI research, incorporating new advancements into Kognitos’ platform.
Requirements
~1 min readBachelor’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 the ability to work in a fast-paced, dynamic
Requirements
~1 min readExperience 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.
What We Offer
~1 min readYou do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills.
Kognitos is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Location & Eligibility
Listing Details
- Posted
- December 19, 2024
- First seen
- May 7, 2026
- Last seen
- May 8, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 28%
- Scored at
- May 7, 2026
Signal breakdown
Please let kognitos know you found this job on Jobera.
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