At a Glance
- Tasks: Build innovative multimodal systems that transform broadcast feeds into real-time insights.
- Company: Join a cutting-edge tech firm leading the way in AI and media technology.
- Benefits: Enjoy competitive pay, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with mentorship opportunities and a focus on continuous improvement.
- Why this job: Make a real impact in the AI space while working with the latest technologies.
- Qualifications: 5-8+ years in software engineering with strong skills in Python, Java, or Rust.
The predicted salary is between 70000 - 90000 £ per year.
About the Role
Senior Applied AI Engineer to build production‑grade, multimodal (audio/video/text) systems that convert broadcast and radio feeds into structured, real‑time signals and event candidates. Implement and evolve “agentic” components (sensor agents, specialist agents, decision logic) powering products like Audio Intelligence, semi‑automated broadcast‑to‑data tagging, and highlight/momentum signals. Use technical expertise and pragmatic problem‑solving in an Agile, continuous‑improvement team. Expect a data‑driven, evidence‑based mindset with continuous experimentation and validation.
Key Responsibilities
- Build and maintain multimodal agents:
- Audio sensor agents (acoustic events, sentiment, alignment)
- Visual sensor agents (scorebug/overlay reading, basic visual cues when applicable)
- Specialist and decision logic components (structured event outputs, confidence, traceability)
- Implement streaming‑friendly pipelines: chunking, normalization, time‑sync, async execution, and robust retry/backoff for model/tool calls.
- Develop prompt‑as‑code with strict JSON contracts, schema validation, and deterministic post‑processing to reduce brittleness.
- Improve system robustness under noisy inputs:
- Design fallback behaviors (degraded modes)
- Add guardrails and confidence thresholds
- Instrument traces/metrics for latency, cost, and accuracy
- Partner with product, platform, and domain leads to translate sport rules and edge cases into validation logic and integrate outputs into downstream consumers (tagging, live feeds, analytics).
- Contribute to the evaluation workflow by adding test cases, failure mode categories, and regression checks for prompts and model routing.
- Stay up‑to‑date with emerging Gen AI technologies, tools, and best practices.
- Mentor and support other team members in data engineering principles and practices.
Qualifications
- 5–8+ years of professional software engineering experience (backend and/or ML systems).
- Strong proficiency in one or more of: Python, Java, Rust.
- Hands‑on experience building production services involving LLM or multimodal model integration (Gemini, ChatGPT, Claude).
- Comfortable with ambiguity, iterative experimentation, and evidence‑based decision‑making in an Agile environment.
- Experience with streaming data platforms like Kafka, Pulsar, Flink.
- Experience with AWS Bedrock or Google Vertex AI.
- Familiarity with version control systems (Git).
- Excellent problem‑solving skills and attention to detail.
- Ability to work independently and as part of a team.
- Strong communication skills.
Preferred Qualifications
- Experience with audio ML/speech/acoustic event detection or media pipelines (audio/video chunking, sync).
- Experience with RAG or rules/config grounding for sport‑specific logic (league configs, terminology, rulebooks).
- Familiarity with evaluation practices (golden sets, precision/recall, drift monitoring) and production observability.
- Experience operating systems where cost/latency tradeoffs matter (routing “flash vs heavy” models, caching, batching).
Travel & Working Model
Occasional travel may be required. Hybrid working models differ based on role and location.
Disability Assistance
Let us know when you apply if you need any assistance during the recruiting process due to a disability.
Senior Applied AI Engineer in London employer: Genius Sports
As a Senior Applied AI Engineer, you will thrive in a dynamic and innovative environment that champions continuous improvement and data-driven decision-making. Our company fosters a collaborative work culture where your expertise will be valued, and you'll have ample opportunities for professional growth through mentorship and exposure to cutting-edge technologies. Located in a vibrant area, we offer a hybrid working model that promotes work-life balance while engaging in meaningful projects that shape the future of AI in broadcasting.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Applied AI Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving multimodal systems or AI. This gives you a chance to demonstrate your expertise beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on your problem-solving skills. Be ready to tackle real-world scenarios related to audio/video/text systems and think through your approach out loud. It’s all about showing your thought process!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Senior Applied AI Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Applied AI Engineer role. Highlight your experience with multimodal systems and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Showcase Your Projects:Include specific examples of your work, especially those involving audio, video, or text processing. If you've built production services or worked with LLMs, let us know! This helps us understand your hands-on experience.
Be Clear and Concise:When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to read. We appreciate a well-structured application that gets straight to the good stuff!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, we love seeing applications come in directly from our site!
How to prepare for a job interview at Genius Sports
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, Java, and Rust. Brush up on your experience with LLMs and multimodal model integration, as well as streaming data platforms like Kafka or Flink. Being able to discuss your hands-on experience confidently will impress the interviewers.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex problems, especially in an Agile environment. Think about how you’ve implemented robust solutions under noisy inputs or designed fallback behaviours. This will demonstrate your pragmatic approach to challenges and your ability to think on your feet.
✨Familiarise Yourself with the Domain
Since the role involves sports and media, it’s a good idea to brush up on relevant terminology and rules. Understanding the context of the products you’ll be working on can help you translate sport rules into validation logic more effectively during the interview.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the company and the role. Inquire about their current projects, team dynamics, or how they stay updated with emerging Gen AI technologies. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
