Machine Learning Research Scientist

ElastixAI•Seattle, WA

1d•Hybrid

About The Position

About Elastix AI We are building the next-gen AI inference platform. Description Location: Seattle, WA (Hybrid - 3 days/week in office) About ElastixAI: ElastixAI is an early-stage startup poised to revolutionize AI inference infrastructure. We are developing a cutting-edge AI inference solution that dramatically improves efficiency. Our solution is going to dynamically adapt to any deployment, constantly evolving to power the next generation AI use cases. Role Summary: We are looking for a talented Machine Learning Research Scientist to play a key role in designing our core AI inference platform. You will be actively conducting high impact research on novel ML solutions towards the next generation of efficient intelligence platforms. This is a highly interdisciplinary role where you will collaborate closely with our multi-disciplinary team to ensure novel research ideas contribute to delivering optimal AI inference solutions at scale.

Requirements

PhD in Computer Science, Computer Engineering, or a related field.
3+ years of experience leading Machine Learning research initiatives.
Demonstrated history of research with publications in leading conferences and journals.
Experience with generative models such as LLMs and VLMs.
Proficiency in at least one ML framework (e.g., PyTorch, TensorFlow, JAX).
Strong proficiency in one or more programming languages such as Python, or C++.
Strong communication skills and a proven ability to collaborate effectively in a cross-functional team environment.

Nice To Haves

Research experience in ML model efficiency and optimization.
Familiarity with performance analysis, profiling, and optimization techniques.
Experience with cloud platforms (AWS, GCP, Azure).
Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).

Responsibilities

Conduct research, prototype, and implement novel ML techniques to advance state-of-the-art in the generative AI domain.
Define and lead high impact applied research initiatives.
Writing high-quality code, designing and performing experiments, and organizing results.
Work alongside multi-disciplinary engineers to bring research initiatives to production.