### Vision
Stochastic’s vision is to build an efficient AI system where everyone will
have access to personalized AI maximizing our productivity and creativity.
Just as computers evolved from centralized, enterprise-only form factors to
personal computers, we believe in the future of personalized AI that can help
everyone with their day-to-day work. The currently popular approach of scaling
language models infinitely larger taken by the few companies causes
centralization of AI power, does not protect privacy nor leverage
individuality, and further accelerates carbon emission problems. By focusing
on more efficient language models, we call Evolutionary Language Models that
self-improve on user data and interactions, we are planning to deliver a truly
personalized AI that will be your best partner.
### Team
Founded by Harvard University AI systems researchers that built the world's
first Bayesian and LLM inference accelerators and a real-time speech NLP
engine that ran on the edge. Stochastic is joined by AI researchers and
engineers with the passion for making AI more accessible to everyone. Our
recent research includes latency-optimized transformers architecture,
quantized parameter efficient fine-tuning, and sparsity-aware throughput
maximization on GPUs.
### Business
Stochastic serves a diverse range of clients, including Fortune 500 companies
and one of the globe's largest asset managers. Our proprietary technology,
xChat, streamlines the creation of customized LLM chatbots for both automating
customer support and enhancing internal knowledge management, offering the
industry's most cost-effective solutions.
### Role
We are looking for Machine Learning Engineers who are interested in
implementing the best optimization techniques on state-of-the-art ML models.
You should have a strong interest in solving the challenges of accelerating ML
models. You are someone who is research-oriented, deeply knowledgeable of best
practices in your field, and highly self-motivated and directed.
As a Machine Learning Engineer, you will:
* Help design and build the tech stack to ensure high system scalability and reliability
* Finetune, accelerate and deploy LLMs in our existing pipelines
* Conduct research and experiments on latest finetuning and acceleration techniques
* Manage specification, development, testing and releasing of new features
* Provide support for strategic customers on deployment and scalability issues
* Support strategic planning of xChat and xCloud, the two main products of Stochastic
You are a good fit if you have:
* Degree in Computer Science/Machine Learning/Statistics
* Experience with RAG systems
* Experience with Python and MongoDB
* Experience finetuning Deep Learning models with PyTorch and Transformers libraries
* Experience deploying Deep Learning models in production environments
* Experience with at least one the main public cloud providers (AWS, Azure or GCP)
* Experience with Kubernetes
Strong Pluses:
* Experience working on accelerating models
* Experience on distributed systems
* Experience with Terraform
* Past experience working as a ML Engineer at a SaaS company
* Experience overseeing a team
To apply, please send a resume and a paragraph on why you are interested to:
[jobs@stochastic.ai](mailto:jobs@stochastic.ai)
