Sr. Backend Software Engineer (Infrastructure ML Ops)

The posting, as Philo wrote it

At Philo, we’re a group of technology and product people who set out to build the future of television, marrying the best in modern technology with the most compelling medium ever invented — in short, we’re building the TV experience that we’ve always wanted for ourselves. In practice this means leveraging cloud delivery, modern tech stacks, machine learning, and hand-crafted native app experiences on all of our platforms. We aim to deliver a rock solid experience on the streaming basics, while cooking up next generation multi-screen and multi-user playback experiences.

SENIOR BACKEND SOFTWARE ENGINEER (INFRASTRUCTURE MLOPS)

The infrastructure team at Philo builds the foundation for a 24/7 live and on-demand streaming product serving video to our growing subscriber base. It provides a platform that enables groups across the company – such as video delivery, product, support, and analytics – to do their best work easily and smoothly. Our systems are highly distributed, horizontally scalable and run in the cloud on Kubernetes. We continuously test and deploy our code and closely monitor the health and performance of our production environment.

We are seeking an enthusiastic Infrastructure MLOps Software Engineer to help us build and improve the ML infrastructure at Philo. We are building out ML and LLM infrastructure and this role will be pivotal in setting direction, adopting best practices, and shipping infrastructure that will be used across the company.

As a sample, the ML infrastructure supports teams like Discovery in building content recommendation models that will help our users find more favorite shows from the large Philo catalog. The engineering team is designing and developing our own agent harnesses to support coding and empowering everyone at the company to get answers across our code bases, analytics, logs, and communication tools. The video player team is using LLMs to classify ads and label our video catalog so that users have a better experience. You’ll build the serving, evaluation and platform infrastructure that these workloads depend on.

Responsibilities

• Manage the core infrastructure at Philo with a focus on supporting ML and LLM workloads. This infrastructure is relied on by a large subscriber base of Philo’s product as well as internal stakeholders across the company.
• Design, build, and maintain cloud infrastructure components (AWS and Kubernetes) using a combination of in-house technology and open source software.
• Build and scale model serving and inference infrastructure for both real-time recommendation models and LLM workloads — including model servers (e.g. NVIDIA Triton), LLM inference engines (e.g. vLLM, TGI, TensorRT-LLM), autoscaling, and latency/throughput optimization.
• Manage GPU and accelerator infrastructure on Kubernetes — scheduling, capacity and quota management, and cost optimization across on-demand and spot capacity.
• Design, build, and maintain monitoring and observability

[…]
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• Free Gympass subscription — an all-in-one corporate benefit that gives employees the largest selection of gyms, studios, classes, training and wellness apps
• Dog-friendly office
• And much more!

For California Residents: Philo’s CCPA Notice at Collection – Employees, Applicants, Owners, Directors, Officers and Contractors https://about.philo.com/ccpa-notice/

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Use of Automated Tools in Our Hiring Process

We use software tools, including our applicant tracking system (Ashby), to help manage applications for this role. Automated features (i) assess the skills, experience, and qualifications relevant to the role as described in this posting, and (ii) flag applications that appear fraudulent, duplicative, or not genuinely submitted by the applicant.

A summary of the most recent independent bias audit of the automated employment decision tool used in this process, including the audit date and data source, is available here: Bias Audit Summary https://www.philo.com/about/bias-audit-summary.

You may request that a member of our team review a decision through a process that does not rely on the automated tools, or request a reasonable accommodation, by emailing recruiting@philo.com. We will not retaliate against you for exercising your rights.

Information about the type and source of the data our tools collect, our data retention policy, and how these tools were used in evaluating your application is described in our Privacy Notice – Employees,Applicants, Officers, Directors, and Contractors, or available by emailing recruiting@philo.com.

Depending on your state of residence, you may have additional rights, including to an explanation of an adverse decision, correction of inaccurate data, and meaningful human review. To exercise these or ask whether they apply, email recruiting@philo.com. recruiting@philo.com