Who You Are

We are looking for a driven Software Engineer (MLOps) to be a part of our growing AI 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.

You are curious and like to understand technologies and their tradeoffs in depth - providing technical guidance to the team and peers as and when required. Leading by example, you have accumulated a wealth of insights and experiences from your hands-on involvement in the field, and you are committed to rolling up your sleeves and getting work done. You like joining and supporting other engineers in their work to learn from them as well as letting them benefit from your expertise and experience.

You have the motivation and skills to identify technical product needs, initiate projects and owning their delivery, including the involvement of engineering peers as needed. You are comfortable with challenging the status quo respectfully to drive and deliver technical excellence in the team.

**We are seeking a team member located within one of the following areas: USA/Canada/UK/EU

Responsibilities

The AI Platform team you are joining is responsible for building the core platform that powers model training, inference and decision making in our products. Furthermore the team owns MLOps and the services hosting our AI capabilities. Productionizing results from Research, as well as extending our systems and providing support according to our customer needs fall into team responsibilities as well. You will join this team as an experienced engineer with a focus on MLOps solutions to grow our expertise in that area, but also contribute as a software engineer more widely in the team.

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

In particular, you will:

• Design, build and lead the MLOps initiatives and vision for the AI Platform to strengthen automation, orchestration, versioning, observability, monitoring and collaboration for the platform.
• Build and design scalable components for the AI Platform to allow high throughput training and inference for RL 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 clear, extensible software interfaces for the team's customers and maintain a high release quality bar.
• Design and optimize data storage & retrieval mechanisms for high throughput, security & ease of access.
• Perform DevOps duties of CI/CD, Release & Deployment management.
• Be a part of our global production oncall team and, own & operate your services in production, meeting Phaidra’s high bar for operational excellence.
• Lead cross-functional initiatives collaborating with engineers, product managers and TPM across teams.
• Mentor your peers and be a technical role-model in the team.

Onboarding

In your first 30 days…

• You will be immersed in an onboarding program that introduces you to Phaidra and our product.
• You will spend time in the Engineering org, learning how the teams operate, interact, and approach problems.
• You will read various parts of our handbook and familiarize yourself with the documentation culture at Phaidra.
• You will set up your development environment and start working on an onboarding exercise that will introduce you to various parts of our code base.
• You will learn about how we use agile and be able to navigate our sprint boards and backlogs.
• You will learn about various team standards and development & release processes.
• You will start to learn about our system architecture and infrastructure.
• You will start picking up few good “first-tasks” to get yourself accustomed to the end to end release flow.

In your first 60 days…

• You will get a solid understanding of what Phaidra does and how we do it.
• You will meet with team members across Phaidra and started building relationships that will help you be successful at your job.
• You will complete the onboarding exercise and will be on your way to completing your first production task.
• You will take ownership for the MLOps work on the team, identify gaps and propose roadmap items on the topic.

In your first 90 days…

• You will be fully integrated in the team and with team members across the company.
• You will have a more in-depth understanding of our system architecture and infrastructure.
• You will complete your first on-call experience helping monitor and improve our production environments.
• You will become an expert with our tooling.
• You will start to contribute to knowledge sharing throughout Phaidra and the team.
• You will take proactively drive MLOps topics in the team and represent it technically throughout the company.

Key Qualifications

• 7 years of work experience.
• Bachelors or Masters in Computer Science, or equivalent experience.
• Strong experience on designing and implementing MLOps solutions for AI production systems
• Expertise with production Software Engineering - relational and non-relational data modelling, micro-services, understanding of event driven systems, etc.
• Strong experience building large scale multi-tenant systems with high availability, fault tolerance, performance tuning, monitoring, and statistics/metrics collection.
• Strong expertise in Python and Cloud environments
• Good grasp of Machine Learning (especially Deep Learning) fundamentals.
• Ability to collaborate and communicate effectively in an all-remote setting
• Doing your work with curiosity, ownership, transparency & directness, outcome orientation, and customer empathy.

Bonus

• Experience as a service owner of a realtime production system - operating & monitoring services in production, including using observability tooling such as Prometheus, Grafana, Tempo or equivalent offerings and incident management.
• Experience with building applications that can be deployed in cloud, hybrid or on prem environments
• Exposure to Reinforcement Learning

Our Stack

• Languages - (Backend) Python, Go; (Frontend) JavaScript/TypeScript, React; Customer SDK & Clients - C# .NET
• PyTorch
• Cypress
• Docker, Kubernetes, Terraform &Kapitan
• Gitlab CI, ArgoCD, Atlantis, Vercel
• GCP - GKE, PubSub, CloudSQL, BigTable, Postgres, etc.
• Ray.io
• REST & gRPC micro-services
• Poetry, Pantsbuild

General Interview Process

All of our interviews are held via Google Meet, and an active camera connection is required.

1. Initial screening interview with a People Operations team member (30 minutes): The purpose of this interview is to meet you, learn more about your background, and discuss what you are looking for in a new position.
2. Hiring manager interview (30 minutes): The purpose of this meeting is for you to get to know the manager for the role. This chat will mainly focus on your previous experience and technical background. You can expect to talk about projects that you have worked on in the past and ask any questions about the team & role.
3. Technical Interview 1 (60 minutes): The purpose of this interview is to assess your skills in Machine Learning and related mathematics.
4. Technical Interview 2 (90 minutes): In this interview, we will go over a real world MLOps problem. You can expect to draw architecture diagrams using boxes & arrows in your browser. We will talk about system design, scalability and monitoring.
5. Meeting with VP of Engineering (30 minutes): This interview is a combination of technical and cultural fit assessment. You will cover the technical experience and the skills that you brinand have an opportunity to ask any questions about the team’s culture or vision.
6. Culture fit interview with Phaidra’s co-founders (30 minutes): This interview focuses on alignment with Phaidra’s values

Base Salary

US Residents: $115,200-$208,800/year

UK Residents: £96,400-£144,000/year

This position will also include equity.

These are best faith estimates of the base salary range for this position. Multiple factors such as experience, education, level, and location are taken into account when determining compensation.