How to prepare for a career in broadcasting tech: skills bootcamp plan based on streaming growth

Ready for broadcasting tech but not sure where to start? This 12-week bootcamp plan gets you job-ready for streaming-platform roles in 2026

Competition for graduate and entry-level roles in streaming is fierce — and platforms now expect demonstrable, practical skills, not just theory. You need a portfolio that proves you can build resilient video pipelines, optimise encodes and run operations at event scale. This guide gives a compact, hands-on 12-week learning and project plan that covers CDN basics, video encoding, observability, ops tooling and event-scale simulations — all tuned to the realities of 2026 streaming growth.

Why this matters in 2026: industry context and the opportunity

Late 2025 and early 2026 cemented a big trend: huge live events and regional streaming booms are creating permanent demand for engineers who understand the plumbing of streaming. Variety reported that JioHotstar (JioStar) averaged around 450 million monthly users and attracted 99 million digital viewers for a single cricket final in late 2025 — a reminder that single events can create enormous load spikes for platforms.

Variety: JioHotstar reached 99 million viewers for a single match and averaged 450M monthly users in late 2025.

At the same time, technical shifts are making specialised skills more valuable: wider adoption of AV1 and hardware-assisted AV1 encoders, CMAF + HLS/DASH convergence, low-latency WebRTC for interactive streaming, and cloud-edge architectures that push packaging and personalization closer to viewers. Employers now shortlist candidates who show they can design CI/CD for media pipelines, implement SRE practices, and run realistic load tests for major events.

How to use this plan

This plan is for students, interns and graduates aiming for junior engineering roles at streaming platforms, CDNs, or media-tech startups. Each week includes:

• Learning objectives (concepts and commands)
• Hands-on tasks and minimal viable deliverables (MVDs)
• Portfolio suggestions and interview talking points

Use a GitHub repo or a portfolio site to track week-by-week deliverables and write short case-study notes describing trade-offs. Aim to show 3–4 polished demo projects by week 12.

The 12-week broadcasting tech bootcamp

Week 1 — Foundations: video basics and modern streaming formats

Learning objectives: key formats, containers and the streaming stack (container: MP4/ISOBMFF, HLS, DASH, CMAF), bitrate ladders and adaptive streaming basics.

• Hands-on: Install FFmpeg and create HLS/DASH renditions from a test video. Produce 3 bitrate renditions (240p/720p/1080p) and inspect manifests.
• MVD: A GitHub repo with FFmpeg commands and generated HLS/DASH files, plus a short README explaining the bitrate ladder.
• Interview angle: Explain ABR, manifests and why CMAF matters for unified HLS/DASH delivery.

Week 2 — Video encoding deep dive

Learning objectives: codecs (H.264, H.265/HEVC, AV1), encoding parameters (CRF/bitrate, GOP, keyframe intervals), CPU vs hardware encoders, and per-title encoding concepts.

• Hands-on: Create encodes with x264, x265 and SVT-AV1 (or libaom if SVT-AV1 unavailable). Measure quality vs bitrate using PSNR/SSIM and VMAF (install libvmaf).
• MVD: A short report showing bitrate-quality plots and recommendations for three content types: sports, talk-show, and animation.
• Interview angle: Discuss trade-offs (encode time, cost, latency) and when to choose AV1.

Week 3 — Packaging and DRM basics

Learning objectives: segmenters/packagers (Bento4, Shaka Packager), CMAF pros/cons, and an intro to DRM concepts (Widevine, PlayReady).

• Hands-on: Use Shaka Packager or Bento4 to package your renditions into CMAF fragments and create HLS/DASH manifests. Add simple encryption (test keys) to simulate DRM packaging.
• MVD: A demo site (static or small Node server) that serves packaged assets with manifest examples.
• Interview angle: Clarify how packaging affects latency and cacheability.

Week 4 — CDN basics and caching principles

Learning objectives: HTTP caching headers, origin vs edge, cache-control, stale-while-revalidate, and CDN topology basics. Understand TTLs for live vs VOD content.

• Hands-on: Spin up a small origin (nginx) to serve your packaged content. Configure caching headers and simulate an edge with another nginx instance acting as reverse-proxy cache.
• MVD: Diagrams of a simple CDN and a working demo showing cache hit/miss behaviour.
• Interview angle: Explain how CDN placement and caching strategies reduce origin load during spikes.

Week 5 — Live streaming fundamentals

Learning objectives: ingest protocols (RTMP, SRT, WebRTC), ABR for live, latency sources, and live packaging (segmenter-to-edge pipeline).

• Hands-on: Use OBS or ffmpeg to push a live test stream to an open-source media server (NGINX-RTMP, mediasoup or Janus). Package to HLS/DASH on the fly if possible.
• MVD: Recorded video demonstrating live ingestion, packaging and playback. Note end-to-end latency and where it can be optimised.
• Interview angle: Describe how you would reduce latency for sports vs social streaming.

Week 6 — Cloud-native streaming and edge computing

Learning objectives: containerise media services, basics of Kubernetes for media, and edge compute patterns (Cloudflare Workers, AWS Lambda@Edge or similar).

• Hands-on: Containerise your packager/transcoder (simple Dockerfile). Deploy to a local Kubernetes cluster (kind or minikube). Add an ingress that mimics an edge behaviour.
• MVD: Kubernetes manifests and a README explaining scaling considerations at edge vs origin.
• Interview angle: Talk about pros/cons of performing personalization at the edge.

Week 7 — Observability, logging and SRE basics

Learning objectives: golden signals (latency, traffic, errors, saturation), tracing, and log aggregation for media apps.

• Hands-on: Add Prometheus metrics to a simple service (or use an exporter). Use Grafana to visualise bandwidth, request rates and error rates. Centralise logs with Loki or ELK.
• MVD: A dashboard that shows at-a-glance health for your mini streaming platform and a sample runbook for an incident (origin overloaded).
• Interview angle: Describe a post-mortem from your runbook — cause, mitigation and prevention.

Week 8 — Ops tooling and CI/CD for media pipelines

Learning objectives: automated builds for codecs, CI for packaging, and safe deployments (canaries, blue-green, Argo Rollouts).

• Hands-on: Add a GitHub Actions pipeline that runs unit tests and builds Docker container for your packager. Simulate a canary deployment in minikube or use Argo Rollouts.
• MVD: CI pipeline definition and a short video showing a canary rollout and rollback.
• Interview angle: Explain how CI reduces risk when changing encoding configurations.

Week 9 — Security, compliance and cost control

Learning objectives: transport-layer security, tokenised URLs, bandwidth-cost strategies and student-friendly cloud credits (AWS/Azure/Google offers).

• Hands-on: Implement signed URLs or token-based protection on your origin. Add basic cost-estimate notes for serving 1M minutes of video from a cloud provider.
• MVD: Security checklist and a cost comparison for single-region vs multi-region edge delivery.
• Interview angle: Talk about ways to mitigate leeching and unexpected cost spikes.

Week 10 — Event-scale simulations and chaos engineering

Learning objectives: distributed load testing, network impairment, and chaos testing for resilience (failure injection).

• Hands-on: Use k6 or Locust to create a distributed load test that simulates thousands of concurrent video viewers. Shape network conditions with netem or Toxiproxy to simulate packet loss and latency.
• MVD: A load-test report showing throughput, 95th/99th percentile latencies, error rates and the effect of toggling caching or increasing origin capacity.
• Interview angle: Be ready to describe the scenario you tested and one operational change you made to improve resilience.

Week 11 — AI and optimisation: per-title encodes and QoE

Learning objectives: automated per-title encoding strategies, live bitrate adaptation with ML signals, and perceptual quality metrics (VMAF).

• Hands-on: Implement a simple per-title encode pipeline: analyse content complexity, choose bitrate ladder, and produce encodes. Benchmark VMAF per bitrate.
• MVD: Case study comparing a static ladder vs per-title ladder and showing bandwidth savings for the same QoE.
• Interview angle: Explain a simple model for choosing bitrate ladders and how you validated it.

Week 12 — Final project week: integrate, present, and polish

Learning objectives: combine components into a small end-to-end demo for your portfolio; prepare interview materials.

• Hands-on: Build an end-to-end mini-platform: ingest -> packager -> origin -> edge cache -> player. Add monitoring and a simple CI pipeline. Run a scaled load test and document results.
• MVD: Public GitHub repo with a clean README, recorded demo video (3–5 minutes), architecture diagram, and a one-page post-mortem with lessons learned.
• Interview angle: Walk interviewers through trade-offs, the scale you simulated, and one operational improvement you would make in production.

Projects that get attention from recruiters

Recruiters and hiring managers in streaming want projects that demonstrate applied skills, problem solving and communication. Make sure at least one of these appears in your portfolio:

• Mini CDN demo: nginx origin + edge cache + metrics that show cache hit improvements and origin load reductions.
• Live ingest to low-latency player: show end-to-end latency numbers and how you reduced them.
• Per-title encoding case study: measurable bandwidth savings at equal or better VMAF.
• Event-scale load test with public report: show how your system behaves under 10k/100k concurrent viewers (simulated).

Essential tools and learning resources

Tools you'll use weekly: FFmpeg, Shaka Packager/Bento4, x264/x265/SVT-AV1, NGINX (or an open-source media server), Docker, Kubernetes (kind/minikube), Prometheus, Grafana, k6/Locust, GitHub Actions, and network tools (tc/netem).

Use official docs and community tutorials for each tool. For codec and quality metrics, the Netflix VMAF repo is essential reading. For real-world context, read recent streaming case studies — 2025 and 2026 event post-mortems often explain failure modes and mitigation strategies that are great interview fodder.

How to turn this into internships and graduate job wins

1. Document everything: weekly write-ups make great case studies on your CV and LinkedIn.
2. Open-source your configurations: hiring teams love reproducible demos.
3. Target local opportunities: London has many media-tech startups, CDNs and broadcasters — tailor your CV with borough-level availability and commuting preferences if asked.
4. Prepare 3 stories: one technical, one incident/recovery, and one cost-optimisation story. Use the STAR format in interviews.
5. Apply early and apply often: include links to demos and a 3-minute explainer video in your applications.

Assessment rubric: what to show a hiring manager

When you apply for graduate roles, hiring teams will look for:

• Practical ability: Can you run a pipeline and explain your choices?
• Systemic thinking: Do you understand caching, origins, and cost trade-offs?
• Operational maturity: Do you have monitoring, runbooks and CI/CD?
• Communication: Can you tell a clear, concise story about a problem and your fix?

Score yourself on each item and include a one-paragraph improvement plan in your portfolio.

London-specific tips for students and interns

• Look for internships with broadcasters (BBC, ITV, Sky), CDNs and streaming startups — many run grad schemes that value demonstrable projects.
• Attend London meetups and conferences focused on streaming and cloud-native media — speaking or demoing an early project gets attention.
• Be ready to discuss visa/relocation in applications. Many employers expect candidates to clarify right-to-work upfront.
• Use student cloud credits (AWS/Azure/Google) to run larger load tests — keep track of cost so you can present a cost vs performance story.

Advanced strategies and future-facing skills (2026+)

To stand out, learn these trends:

• Edge packaging and personalization: moving session-level packaging to the edge so adverts and personalization are inserted closer to viewers.
• AI-driven quality control: automatic anomaly detection for QoE and automated per-title decisions.
• Universal low-latency stacks: familiarity with CMAF low-latency, WebRTC integrations and hybrid approaches.
• Energy and cost-aware encoding: balancing carbon and cost metrics in encoding pipelines is increasingly relevant to employers.

Quick checklist before interviews

• Repo link with 2–3 clear demos and a README summarising technical trade-offs.
• One-pager for each demo: problem, approach, metrics, lessons.
• Prepared answers for incident management, SLOs and cost trade-offs.
• Ability to run a short live demo (or pre-recorded) within 5 minutes.

Closing: your 12-week sprint to a broadcasting tech role

In 2026, streaming platforms reward engineers who can join the team and immediately help deliver reliable, cost-conscious live and VOD experiences. This 12-week plan turns theory into demonstrable, interview-ready projects: from encoding and packaging to CDN design, observability and event-scale simulations. Use each week to build a tight case study, and by week 12 you will have the portfolio, the metrics and the operational thinking employers want.

Ready to start? Fork a repo, reserve an afternoon to run week 1, and schedule a 30-minute video walkthrough you can share with recruiters. If you want a ready-made checklist or a London-focused internship list tailored for broadcasting tech, visit joblondon.uk for curated roles, networking events and resources to help you apply.

Call to action

Start your 12-week bootcamp today. Create your repo, publish a week 1 demo and tag it 'broadcasting-tech-bootcamp-2026'. Want personalised feedback on your portfolio or help preparing for interviews? Submit your repo link at joblondon.uk and we will review it with actionable suggestions tailored to London grad roles.

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