About Us
We are pushing the boundaries of machine learning, reasoning, and computational intelligence, pioneering scientific breakthroughs with next-generation AI models. Join us to innovate in a research-driven environment, exploring ideas that go beyond the capabilities of today’s AI. Be part of a culture of excellence, where breakthroughs, curiosity, and impact matter above all.
Open Positions
Research Scientist
As a Research Scientist at AAI you will find yourself innovating across the full AI stack (data, models, training objectives, inference time algorithms) and adding new components to it.
We are seeking exceptional talent—only stellar individuals need apply. If you thrive on tackling unsolved problems, have a track record of impactful research, and want to work on uncharted scientific challenges, we want to hear from you.
Ready to join our journey of shaping the future of AI? Apply now!
MLOps Engineer
As an MLOps Engineer at AAI you will find yourself building the infrastructure behind cutting-edge reasoning models, which push the boundaries of AI’s ability to reason, learn, and solve complex problems, while improving accuracy.
We are seeking exceptional talent—only stellar individuals need apply. If you thrive on tackling complex engineering problems, have a passion for building scalable ML systems, and wish to advance the state-of-the-art in AI technology, we want to hear from you.
Key Responsibilities:
- Build and maintain our core ML infrastructure.
- Automate and optimize complex ML workflows, transforming them into efficient, scalable processes.
- Collaborate with researchers and engineers to integrate and enhance ML model performance.
- Gain deep expertise in LLM infrastructure, learning how to manage and scale advanced AI systems.
Requirements:
- Degree in Computer Science (or equivalent experience) with a strong passion for learning.
- Proficient in Python and familiar with ML frameworks.
- Experience with Kubernetes and containerization (Docker).
- Exposure to scalable systems (e.g., handling large datasets, distributed computing, multi-user environments).
- Strong problem-solving skills and enthusiasm for tackling technical challenges.
- Excellent communication and collaboration skills.
- A service-oriented mindset, proactively identifying and solving infrastructure needs.
Advantages:
- Familiarity with ML frameworks (PyTorch, TensorFlow, vLLM, TGI, MegatronLM, NVIDIA NeMo)
- Familiarity with profiling tools for GPUs such as NVIDIA Nsight Systems.
- Experience with cloud platforms (AWS, GCP) and CI/CD pipelines.
- Prior experience in ML infrastructure (internships, projects, or work experience)
Ready to join our journey of shaping the future of AI? Apply now!
First step: Click on the button and complete the questionnaire
Senior Software Engineer (Infrastructure/Backend)
As a Senior Software Engineer at AAI you will find yourself building the infrastructure behind cutting-edge reasoning models, which push the boundaries of AI’s ability to reason, learn, and solve complex problems, while improving accuracy.
We are seeking exceptional talent—only stellar individuals need apply. We are looking for candidates that thrive on solving complex distributed computing challenges, designing high-performance infrastructure, and optimizing large-scale systems. If you are passionate about building reliable, scalable tools to support cutting-edge AI we want to hear from you.
Key Responsibilities
- Design and implement scalable, high-performance systems to support ML research workflows.
- Automate complex ML processes, streamlining infrastructure for efficiency and reliability.
- Optimize distributed systems for handling large-scale data processing and ML workloads.
- Collaborate closely with researchers and engineers to define and execute our ML infrastructure roadmap.
Requirements:
- BSc/MSc in Computer Science or related field.
- Proficiency in Python, with experience in system design and backend development.
- Hands-on experience with Kubernetes and containerization technologies (Docker).
- Proven track record of building and maintaining scalable, production-grade systems.
- Strong problem-solving skills and a passion for tackling complex engineering challenges.
- Excellent communication skills and a collaborative approach to teamwork.
Advantages:
- Knowledge of Linux internals.
- A background in large-scale distributed computing or ML infrastructure design.
- Familiarity with cloud platforms (AWS, GCP) and CI/CD pipelines.
- Knowledge of NoSQL databases (e.g. MongoDB).
- Knowledge of monitoring and logging tools (e.g., Prometheus, Grafana).
- Experience with ML frameworks (e.g., PyTorch, TensorFlow) and LLM tools (e.g., vLLM, TGI, NVIDIA NeMo).
Ready to join our journey of shaping the future of AI? Apply now!
First step: Click on the button and complete the questionnaire