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Blue Rose Research

Software Engineer (ML Infra)

Reposted Yesterday
Easy Apply
Remote
Hiring Remotely in USA
130K-170K Annually
Mid level
Easy Apply
Remote
Hiring Remotely in USA
130K-170K Annually
Mid level
The Software Engineer will develop machine learning infrastructure, optimize models, and create tools for data analysis while collaborating with a diverse team.
The summary above was generated by AI

Blue Rose Research develops a wide range of cutting-edge products used by the most important progressive organizations in the country. Our research informs short-term and long-term strategy for advancing progressive causes and has a trusted track record among key decision makers.

The team has a storied history, and has worked with central players to develop strategy and direct hundreds of millions of dollars of resources. The work produced by Blue Rose Research is widely regarded as among the most technically sophisticated in the space. If you join us, you’ll be plugging into a diverse team of engineers, data scientists, and political analysts, who are closely connected to some of the most important decision makers in the progressive ecosystem.

We are looking for a software engineer with extensive machine learning infrastructure and operations experience.

We offer a competitive salary, medical, dental, and health benefits, and a work environment that will support your differences. While the work is remote, we do have an office in NYC and a number of folks who work in-person regularly – both in NYC and at shared workspace meetups in DC. Most of our work happens on East Coast time. 

You will:

  • Collaborate with Data Scientists to design, develop, and implement highly sophisticated model training and evaluation workflows. The goal is to provide a flexible, scalable, and cost-effective infrastructure that enables rapid iteration and experimentation for our data science teams, ultimately accelerating the deployment of cutting-edge models into production.
  • Optimize machine learning models built with JAX and TensorFlow.
  • Work on all parts of the data processing stack, from the initial data ingestion and cleaning, through model training, model evaluation, and model inference.
  • Manage many variations of different models and model configurations supporting custom research on tight deadlines.
  • Build tools to empower data analysts to derive insights from model outputs.
  • Stay focused on building effective tools for data scientists and data analysts without getting distracted by shiny engineering problems.

Our ideal candidate likely:

  • Has deep experience optimizing ML systems for GPUs and CPUs.
  • Knows JAX or similar tools inside and out.
  • Regularly works with Data Scientists to build complex model training and data processing workflows.
  • Understands the ins and outs of fine-tuning transformer models.
  • Dreams about optimizing BigQuery-based ETL pipelines.
  • Slices and dices data with a variety of tools such as Pandas, SQL, and dplyr.
  • Is familiar with a variety of machine learning and statistical techniques.
  • Has a solid DevOps toolkit including Docker, Kubernetes, Terraform, etc.
  • Has strong oral and written communication skills, especially in a remote environment.
  • Is a kind person and a team player who contributes to a warm working environment.

We don’t expect every applicant to have expertise in every area listed above. We encourage you to apply if you don’t feel your experience and background sound like a perfect fit. Many of our team members have taken an unusual path to get to where they are today, and our unique and diverse perspectives make us more effective. We also believe strongly in our team’s ability to learn and excel at new skills and challenges. Join us!

The salary range for this position is $165,000 - $210,000 annually, commensurate with experience.

Candidates must be authorized to work lawfully in the United States.

Top Skills

Docker
Dplyr
Jax
Kubernetes
Pandas
SQL
TensorFlow
Terraform
HQ

Blue Rose Research New York, New York, USA Office

New York, NY, United States

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