Subconscious has developed a computationally intensive service to understand causality on a level with current state-of-the-art experiments. As we continue to grow, our feature set will become increasingly complex, requiring cloud infrastructure to support our increasing number of compute tasks. We are looking for a talented Senior Machine Learning Engineer (MLOps) to join our remote team of fullstack, cloud infrastructure, and frontend developers in scaling and deploying Machine Learning models.

Who We Are: is a Self Supervised Learning company that enables AI-Safe reasoning about cause and effect at scale. We have used our platform to augment existing experiments, identify dubious claims in published research, and perform novel research.

What The Job Entails:

As the Senior Machine Learning Engineer, you will architect and build ML pipelines. You will train, deploy, infer, and monitor ML models, own MLOps, integrate Machine Learning solutions as microservices with applications in production, and setup Model Management Systems.


  • Designing and implementing mission critical software infrastructure on GCP, Azure, Metaflow, and other platforms
  • Collaborating with ML engineers, data scientists, and a team of engineers to design, develop, and implement solutions
  • Leveraging open source tools and building frameworks and components to improve and scale our Serving and ML platform
  • Managing, designing, and developing secure and scalable back-end systems


  • 10+ years infrastructure and related experience
  • 3+ years experience in MLOps, building Machine Learning Platform Solutions
  • Broad and deep experience solving complex problems with technology and with a wide range of databases, platforms, and other technologies
  • Extensive experience in both architecting and the hands on implementation of infrastructure
  • Have deployed at least five large scale services from scratch
  • Experience in Postgres, Redis, GCP, Kafka, Python, R, SQL and NoSQL Databases, Spark, Scikit-Learn, Keras/TensorFlow, PyTorch, AWS Cloud, Lambda & Step functions, Docker, CI/CD Pipelines, Git, and developing APIs
  • Computer Science Degree or related field
  • 5 or more years of industry experience building scalable services and data driven platforms
  • Expertise in SRE, Network, scaling, performance tuning & troubleshooting
  • Experience building and scaling systems both on premise and the cloud
  • Expertise in developing AI/ML Platforms
  • Experience with building ML infrastructure, writing production level code, & deploying Machine Learning models
  • Strong technical leadership skill and proven experience architecting, developing and deploying internet-scale, distributed, and critical services
  • Experience working on complex problems and systems where scalability and performance are very important
  • Strong problem solving and debugging skills We are looking for entrepreneurial individuals who are passionate about AI ethics and causality. If this sounds like you, we'd love to hear from you!