Kognitos
Early-Career Applied ML Engineer
Are you excited about working on cutting-edge AI solutions, building next-generation enterprise automation, and growing your skills in a fast-paced environment? Join Kognitos as an Early-Career Applied ML Engineer to help shape the future of software, tackling challenging problems in AI and enterprise automation. What You'll Work On
Efficient Fine-Tuning Develop methods that reduce resource usage while training and fine-tuning AI models-ensuring high performance without compromising efficiency. Agentic Workflows Advance AI workflows where systems can reason, plan, and execute tasks reliably, minimizing errors and runtime surprises. Multimodal Language Models Contribute to projects combining text, images, and other data types, enabling adaptive enterprise automation solutions. Scalable AI for Enterprises Help address large-scale enterprise needs, creating AI solutions that can significantly reduce operational expenses. Responsibilities
Model Development & Deployment Design, implement, and deploy machine learning models with an emphasis on deterministic task execution and agentic workflows. Multimodal Applications Work on integrating diverse data formats (e.g., text, images) into AI models tailored to real-world enterprise use cases. Resource Optimization Explore and refine fine-tuning techniques to optimize resource usage and improve overall model performance. Compliance & Value Delivery Ensure AI systems adhere to regulatory policies, maintain reliability, and deliver measurable business value. Cross-Functional Collaboration Partner with product, engineering, and business teams to align AI solutions with strategic objectives. Continuous Learning Stay current with AI advancements and apply the latest research insights to enhance Kognitos' platform. Requirements
Educational Background Master's or Ph.D. in Computer Science, Machine Learning, or a related field. Production ML Experience Demonstrated experience developing and deploying machine learning models (via research, internships, or prior roles). Expertise in Fine-Tuning & Large-Scale Models Familiarity with strategies to optimize large language models (LLMs) and manage resource usage efficiently. Programming Skills Proficiency in Python and experience with one or more ML frameworks (e.g., TensorFlow, PyTorch). Problem-Solving Mindset Ability to address complex challenges in a fast-paced, dynamic environment. Preferred Qualifications
Agentic Workflows & Multi-Agent Systems Exposure to or interest in advanced AI topics (e.g., multi-agent systems, reinforcement learning). Enterprise Automation Experience Understanding of automation pain points in large-scale enterprise contexts. Cloud & Distributed Computing Familiarity with cloud platforms (AWS, GCP, Azure) and distributed ML frameworks like Spark, Ray, or Kubernetes. Why Join Kognitos?
Tackle the Hardest AI Problems Engage in meaningful work, solving critical challenges within a trillion-dollar hyper-automation market. Significant Impact Build AI systems that can save enterprises up to 30% in operational costs. Growth & Mentorship Collaborate with a world-class team, gaining direct mentorship from seasoned engineers and researchers. Cutting-Edge Environment Work with the latest AI innovations and see your contributions influence major enterprise transformations. Ready to build the future of enterprise automation? Apply now and bring your passion for AI to Kognitos. This is your opportunity to join a top-tier team, push the boundaries of AI research, and make a direct impact on how businesses operate worldwide. Final note
You 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. Equal opportunities provider
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.
Are you excited about working on cutting-edge AI solutions, building next-generation enterprise automation, and growing your skills in a fast-paced environment? Join Kognitos as an Early-Career Applied ML Engineer to help shape the future of software, tackling challenging problems in AI and enterprise automation. What You'll Work On
Efficient Fine-Tuning Develop methods that reduce resource usage while training and fine-tuning AI models-ensuring high performance without compromising efficiency. Agentic Workflows Advance AI workflows where systems can reason, plan, and execute tasks reliably, minimizing errors and runtime surprises. Multimodal Language Models Contribute to projects combining text, images, and other data types, enabling adaptive enterprise automation solutions. Scalable AI for Enterprises Help address large-scale enterprise needs, creating AI solutions that can significantly reduce operational expenses. Responsibilities
Model Development & Deployment Design, implement, and deploy machine learning models with an emphasis on deterministic task execution and agentic workflows. Multimodal Applications Work on integrating diverse data formats (e.g., text, images) into AI models tailored to real-world enterprise use cases. Resource Optimization Explore and refine fine-tuning techniques to optimize resource usage and improve overall model performance. Compliance & Value Delivery Ensure AI systems adhere to regulatory policies, maintain reliability, and deliver measurable business value. Cross-Functional Collaboration Partner with product, engineering, and business teams to align AI solutions with strategic objectives. Continuous Learning Stay current with AI advancements and apply the latest research insights to enhance Kognitos' platform. Requirements
Educational Background Master's or Ph.D. in Computer Science, Machine Learning, or a related field. Production ML Experience Demonstrated experience developing and deploying machine learning models (via research, internships, or prior roles). Expertise in Fine-Tuning & Large-Scale Models Familiarity with strategies to optimize large language models (LLMs) and manage resource usage efficiently. Programming Skills Proficiency in Python and experience with one or more ML frameworks (e.g., TensorFlow, PyTorch). Problem-Solving Mindset Ability to address complex challenges in a fast-paced, dynamic environment. Preferred Qualifications
Agentic Workflows & Multi-Agent Systems Exposure to or interest in advanced AI topics (e.g., multi-agent systems, reinforcement learning). Enterprise Automation Experience Understanding of automation pain points in large-scale enterprise contexts. Cloud & Distributed Computing Familiarity with cloud platforms (AWS, GCP, Azure) and distributed ML frameworks like Spark, Ray, or Kubernetes. Why Join Kognitos?
Tackle the Hardest AI Problems Engage in meaningful work, solving critical challenges within a trillion-dollar hyper-automation market. Significant Impact Build AI systems that can save enterprises up to 30% in operational costs. Growth & Mentorship Collaborate with a world-class team, gaining direct mentorship from seasoned engineers and researchers. Cutting-Edge Environment Work with the latest AI innovations and see your contributions influence major enterprise transformations. Ready to build the future of enterprise automation? Apply now and bring your passion for AI to Kognitos. This is your opportunity to join a top-tier team, push the boundaries of AI research, and make a direct impact on how businesses operate worldwide. Final note
You 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. Equal opportunities provider
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.