Software Engineer (AI Services)

About Phaidra

Phaidra is building the future of industrial automation.

The world today is filled with static, monolithic infrastructure. Factories, power plants, buildings, etc. operate the same they've operated for decades — because the controls programming is hard-coded. Thousands of lines of rules and heuristics that define how the machines interact with each other. The result of all this hard-coding is that facilities are frozen in time, unable to adapt to their environment while their performance slowly degrades.

Phaidra creates AI-powered control systems for the industrial sector, enabling industrial facilities to automatically learn and improve over time. Specifically:

• We use reinforcement learning algorithms to provide this intelligence, converting raw sensor data into high-value actions and decisions.
• We focus on industrial applications, which tend to be well-sensorized with measurable KPIs — perfect for reinforcement learning.
• We enable domain experts (our users) to configure the AI control systems (i.e. agents) without writing code. They define what they want their AI agents to do, and we do it for them.

Our team has a track record of applying AI to some of the toughest problems. From achieving superhuman performance with DeepMind's AlphaGo, to reducing the energy required to cool Google's Data Centers by 40%, we deeply understand AI and how to apply it in production for massive impact.

Phaidra is based in the USA but 100% remote; we do not have a physical office. We hire employees internationally with the help of our partner, OysterHR. Our team is currently located throughout the USA, Canada, UK, Norway, Italy, Spain, Portugal, Japan, Singapore, and India.

**Please only apply to one opening. If you are a better fit for another opening, our team will move your application. Candidates who apply to multiple openings will not be considered.**

Who You Are

We are looking for a driven Software Engineer (Backend) to be a part of our growing Data Platform team. You are bold and creative, and have deep empathy for customers who may not be tech-savvy. You will design and implement significant parts of the code base and will have the opportunity to make an immediate impact with your work and guide the product and team as we grow.

The Data platform team at Phaidra is responsible for -

• Building streaming & batch components that power both realtime & historical data ingestion & processing
• Building and optimizing the data and feature stores
• Building high-throughput and highly-available multi-modal APIs used throughout the organization, from agent training, to realtime inference to user facing applications.
• Building services to fetch and store external third party data (ex. weather forecasts) required for AI training.

*We are seeking a team member located within one of the following areas: USA, Canada, United Kingdom, Ireland, Norway, Spain, Italy, or Portugal. 

• In the United States, we accept applicants located in the following states: California, Colorado, Connecticut, Georgia, Maryland, Minnesota, Missouri, Nebraska, New York, North Carolina, Pennsylvania, South Carolina, Tennessee, Texas, Virginia, Washington. 
• In Canada, we accept applicants located in the following provinces: Ontario, British Columbia, and Alberta.

Responsibilities

As an organization, we strongly believe in expertise across the stack. As such, you will experience flavors of Software Engineering, Distributed Systems, Machine Learning, MLOps and DevOps. In particular, depending on your interest, you will -

• Build scalable components for the Data platform to allow high throughput data ingestion & data processing, which feeds the data into agents doing realtime inference for autonomous control of industrial systems.
• Contribute to the design and implementation of the product backend by writing REST & gRPC API services and scalable event-driven backend applications.
• Design and optimize a secure and efficient system for storing and utilizing data. This includes developing strategies for data management, implementing security measures to protect sensitive information, and continuously monitoring and improving the system's performance to ensure maximum efficiency.
• Design and develop systems to store and serve batch data for agent training or analytics.
• Make the platform deployable in cloud, hybrid and on-prem environments.
• Perform DevOps duties of CI/CD, R