Hiring Media Engineers: The Complete Guide

# Media Engineer

**Location:** San Francisco, CA (Hybrid) · **Employment Type:** Full-time · **Level:** Mid-Senior

## About [Company]

[Company] is a user-generated content platform where 50 million creators share videos and images. We process 10 million+ media uploads daily—everything from quick clips to high-resolution videos—and quality directly impacts creator success.

Fast, high-quality media processing is competitive advantage. When a creator uploads content, they expect it to be available quickly and look great. Our media infrastructure makes that happen at scale.

**Why join [Company]?**

- Work on media processing at creator-platform scale—10M+ daily uploads
- Solve quality-vs-speed tradeoffs across video, image, and audio
- Direct impact on creator experience and platform growth
- Join a 6-person media team within a 150-person engineering org
- Series C company with strong creator community
- Competitive compensation with meaningful equity

## The Role

We're looking for a Media Engineer to help us build world-class media processing infrastructure. You'll work on ingestion pipelines, transcoding, thumbnail generation, and the quality optimization that makes uploaded content look great.

Media processing combines signal processing with systems engineering. You need to understand codecs and quality metrics, but also how to build reliable pipelines that handle millions of files. You'll balance quality against processing time, storage costs, and delivery bandwidth.

The ideal candidate has hands-on media processing experience and understands the tradeoffs between quality, speed, and cost at scale.

## What You'll Work On

### First 30 Days
- Onboard to our media stack, processing pipelines, and quality systems
- Understand our content types, quality requirements, and processing SLAs
- Ship your first improvement (quality, speed, or reliability)

### First 90 Days
- Own a media system component (video, image, or audio processing)
- Contribute to quality or efficiency improvements
- Build or improve processing pipeline components
- Collaborate with product on media features

### First Year
- Lead media initiatives with quality or cost impact
- Architect improvements to our media infrastructure
- Develop new capabilities (new formats, optimization techniques)
- Establish media engineering best practices

## Objectives of This Role

- Improve video quality (VMAF scores) at the same or lower bitrates
- Reduce media processing latency for faster availability
- Optimize encoding for storage and bandwidth costs
- Maintain 99.9% processing reliability
- Scale processing infrastructure for 2x upload growth

## Responsibilities

**Media Processing (50%)**
- Build and optimize video transcoding pipelines
- Implement image processing (resize, crop, optimization)
- Generate thumbnails and preview assets
- Handle audio extraction and processing
- Ensure format compatibility across devices

**Quality & Optimization (30%)**
- Tune encoding parameters for quality/size tradeoffs
- Implement per-content adaptive encoding
- Measure and improve VMAF, SSIM, and other quality metrics
- Optimize for different content types (animation, screen recording, live action)
- Build quality monitoring and alerting

**Infrastructure & Delivery (20%)**
- Design scalable processing architecture
- Optimize processing job distribution
- Integrate with CDN for efficient delivery
- Monitor processing throughput and failures
- Collaborate with infrastructure on compute optimization

## Required Skills and Qualifications

**Technical Skills**
- 4+ years of backend engineering experience
- 2+ years in media processing
- Deep FFmpeg expertise for encoding workflows
- Understanding of video codecs (H.264, H.265, VP9, AV1)
- Image processing experience (format conversion, optimization)
- Pipeline design for high-volume processing
- Proficiency in Python, Go, or similar languages

**Media Knowledge**
- Understanding of quality metrics (VMAF, SSIM, PSNR)
- Familiarity with video containers and formats
- Experience with encoding parameter tuning

**Soft Skills**
- Quality obsession for user-facing content
- Analytical approach to quality/cost tradeoffs
- Collaboration with product and infrastructure teams

## Preferred Skills and Qualifications

- Video streaming experience (HLS, DASH)
- Audio processing experience
- CDN integration and optimization
- Content-adaptive encoding experience
- Background in image processing or computer vision
- Experience with hardware encoding (NVENC, Intel QSV)

## Tech Stack

**Processing:** FFmpeg, ImageMagick, custom encoding tools

**Backend:** Python, Go for pipeline orchestration

**Queue:** SQS, custom job distribution

**Storage:** S3 for media storage, lifecycle policies

**CDN:** CloudFront for delivery

**Infrastructure:** AWS (EC2, Lambda), Kubernetes

**Quality:** VMAF, custom quality monitoring

## Compensation and Benefits

**Salary:** $140,000 - $185,000 (based on experience)

**Equity:** 0.04% - 0.12% (4-year vest, 1-year cliff)

**Benefits:**

*Health & Wellness*
- Medical, dental, and vision insurance (100% covered)
- $100/month wellness stipend
- Mental health support through Modern Health

*Time Off*
- Unlimited PTO with 15-day minimum encouraged
- 11 paid company holidays
- 16 weeks paid parental leave

*Professional Development*
- $2,500 annual learning budget
- Conference attendance (Demuxed, NAB)
- Internal media tech talks

*Financial*
- 401(k) with 4% company match
- Equity refresh grants annually

*Workspace*
- $1,500 home office setup allowance
- Hybrid work (2-3 days in SF office)
- MacBook Pro and equipment of choice

## Engineering Culture

**How we work:**
- Quality obsession—creators depend on their content looking great
- Data-driven encoding decisions
- Continuous improvement of quality/cost metrics
- Collaboration between media and platform teams
- Blameless post-mortems after processing issues

**What we value:**
- Creator experience above all
- Balance between quality, speed, and cost
- Reliability—uploads must process successfully
- Innovation in encoding and optimization
- Work-life balance (on-call is light and well-supported)

## Interview Process

Our interview process typically takes 2 weeks.

- **Step 1: Recruiter Screen** (30 min)
  Background discussion and role overview.

- **Step 2: Technical Screen** (60 min)
  Media fundamentals and backend engineering.

- **Step 3: Media Deep Dive** (75 min)
  Technical discussion about encoding, quality optimization, and your experience.

- **Step 4: System Design** (75 min)
  Design a media processing pipeline.

- **Step 5: Coding Exercise** (60 min)
  Media-related implementation exercise.

- **Step 6: Team Interviews** (2 x 30 min)
  Meet potential teammates.

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*[Company] is an equal opportunity employer.*