AI Research Engineer, Model Optimization and Inference

AI Research Engineer, Model Optimization and Inference

Full-Time 70000 - 90000 £ / year (est.) Home office (partial)
Iconic Interactive

At a Glance

  • Tasks: Architect and build high-performance inference engines for AI-driven virtual actors.
  • Company: Join Iconic, a pioneering startup at the forefront of AI and entertainment.
  • Benefits: Competitive salary, equity, 25 days leave, hybrid work, and a fun culture.
  • Other info: Be part of a dynamic team tackling exciting AI challenges.
  • Why this job: Shape the future of interactive storytelling with cutting-edge AI technology.
  • Qualifications: MSc/PhD in Computer Science or equivalent experience; strong model optimization skills.

The predicted salary is between 70000 - 90000 £ per year.

The Mission

At Iconic, our virtual actors don't just generate “text” or “actions”—they perform. They need to speak, move, and perceive in milliseconds, often running locally on a player's machine alongside a rendering engine. You will bridge the gap between massive research models and the constraints of real‑time interactive entertainment.

The Role

You will architect and build the inference engine that powers our digital entities. Your main task will be tearing apart the model architecture to make it run as fast as possible on consumer hardware while keeping their abilities intact for the intended usage. As part of a small, focused team, you'll have significant autonomy and end‑to‑end ownership. You will work at the intersection of System ML and Game Tech. You might spend one day implementing a custom pruning algorithm for our TTS model, and the next day writing a C++ wrapper to expose that model to our game engine. You will work closely with our Character Research team to ensure that optimization never comes at the cost of the character's soul.

Key Responsibilities

  • Architect Low‑Latency Runtimes: Build and maintain high‑performance inference pipelines for Multimodal LLMs, TTS, and Vision models, targeting both server‑side (H100/A100) and consumer edge (RTX 5090, Apple Silicon) environments.
  • State‑of‑the‑Art Optimization: Implement advanced techniques like Speculative Decoding, KV‑Cache quantization, PagedAttention, and Layer Pruning to minimize Time‑To‑First‑Token (TTFT) and Time‑Per‑Output‑Token (TPOT), maximizing throughput.
  • Model Compression: Lead our efforts in post‑training quantization (AWQ, GPTQ, GGUF) and distillation to fit massive models into consumer VRAM budgets.
  • Engine Integration: Collaborate with the game engineering team to ensure thread‑safe, non‑blocking asynchronous inference within the game loop.
  • Custom Kernel Development: Write custom ops in CUDA, Triton, or Metal when off‑the‑shelf kernels aren't fast enough.

Requirements

  • MSc or PhD in Computer Science, Machine Learning, or a related field (or equivalent industry experience)
  • Strong experience with model optimization techniques (quantization, pruning, distillation, knowledge transfer)
  • Experience with LLM‑specific inference optimizations (KV‑cache management, speculative decoding, attention mechanisms)
  • Proficiency in C/C++
  • Hands‑on experience deploying ML models on‑device or in latency‑sensitive environments
  • Proficiency in Python and deep learning frameworks (PyTorch, JAX, or TensorFlow)
  • Experience with inference optimization tools and runtimes (TensorRT, ONNX Runtime, Core ML, or similar)
  • Strong systems and engineering skills
  • Excellent collaboration and communication skills

Nice to Have

  • Experience with On‑Device AI stacks: ExecuTorch, CoreML, MLX, or ONNX Runtime
  • Experience in CUDA programming
  • Familiarity with non‑NVIDIA compute (AMD/ROCm, DirectML, Vulkan Compute)
  • Background in real‑time systems or game engines (Unreal, Unity) or Real‑Time Rendering
  • Publications or demonstrated work in efficient ML or model compression (NeurIPS, ICML, MLSys, etc.) or open‑source contributions to projects like vLLM, SGLang, llama.cpp, or bitsandbytes

Why Join Us

Be a foundational member of a team innovating at the intersection of AI, art, and storytelling. You'll help shape the research direction, culture, and technical foundations of a company building toward something genuinely new.

What we offer:

  • Competitive salary and equity compensation
  • 25 days annual leave + bank holidays
  • Based in London with hybrid work
  • Inclusive & friendly company culture with socials and game breaks

About Iconic

Iconic Interactive is a seed‑stage startup building AI that breathes life into virtual worlds. The future of entertainment is personal: entire universes shaped around each of us, where you are not watching a story but living at the center of one, shaping it. We're building every layer of intelligence these experiences need: characters that feel and convey meaning, narrators that weave your story, and world directors that act like an ever‑present game master: adapting, orchestrating, surprising. We're a growing team tackling some of the most fascinating problems in AI: creating minds that inhabit and shape new worlds.

AI Research Engineer, Model Optimization and Inference employer: Iconic Interactive

At Iconic, we pride ourselves on being an exceptional employer, offering a unique opportunity to work at the forefront of AI and interactive entertainment in the vibrant city of London. Our inclusive and friendly culture fosters collaboration and creativity, while our commitment to employee growth ensures that you will have the chance to shape your career alongside groundbreaking projects. With competitive salaries, equity compensation, and a healthy work-life balance, including 25 days of annual leave plus bank holidays, joining our team means becoming part of a pioneering journey where your contributions truly matter.

Iconic Interactive

Contact Details:

Iconic Interactive Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land AI Research Engineer, Model Optimization and Inference

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Iconic Interactive!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AI Research Engineer, Model Optimization and Inference at Iconic Interactive.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Iconic Interactive.

Apply Directly through Our Website

When you find a suitable opening like AI Research Engineer, Model Optimization and Inference at Iconic Interactive, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace AI Research Engineer, Model Optimization and Inference

Model Optimization Techniques
Quantization
Pruning
Distillation
Knowledge Transfer
LLM-Specific Inference Optimizations
KV-Cache Management

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Iconic Interactive, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Iconic Interactive. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Iconic Interactive

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Iconic Interactive!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.