Senior Machine Learning Engineer
- £85,000-£110,000
- Start-Up
- Remote based with occasional meet ups in the UK
- Chance to work with industry leading experts
We are currently partnered with a revolutionary start-up looking to bring in a Senior Machine Learning engineering to work with the co-founders and newly appointed CTO. As a tech-driven AI startup, we are at the forefront of cutting-edge technology, leveraging Machine Learning, Generative AI, and real-time data analysis to create impactful solutions. If you’re passionate about innovation and thrive on ambitious goals, you’ll feel right at home here.
The co founders believe that small teams achieve big things. They want to empower individuals create extraordinary outcomes. They are assembling a world-class AI and Engineering team where every contributor has the opportunity to leave a profound impact.
The business is currently in stealth mode although a sprinkle of information we can provide is that the business are building a next generation platform to help improve customer experiences on an unprecedented scale systems process billions of real-time data points daily, combining advanced ML models and large language models to deliver context-aware experiences worldwide. Through rapid model optimisation and continuous experimentation, the company drives engagement through intelligent recommendations and personalised content, delivering over 10%+ revenue growth for their clients & partners.
Key Responsibilities:
As a Machine Learning Engineer, you'll be instrumental in shaping our technical foundation and ML infrastructure. You'll work directly with the founding team to build and scale our AI-driven platform from the ground up.
- Own the end-to-end ML infrastructure, from initial architecture decisions to production deployment, setting the technical standards for our growing team.
- Take the lead in bridging research and production, turning innovative ML concepts into scalable, production-ready systems that process billions of real-time data points.
- Design and implement robust ML pipelines that can handle our rapidly growing data volume while maintaining exceptional performance.
- Build and optimize core model components with a focus on real-world impact, directly contributing to our mission of transforming gaming experiences.
- Drives incremental improvements (across quality, ease of (re)use, performance) within the data, from PoC to production-grade systems that can scale reliably.
- Establish best practices for code quality, testing, and documentation that will shape our engineering culture .
- Create and maintain scalable data pipelines and APIs that can handle increasing complexity while maintaining reliability.
- Works as part of a multi-disciplinary team, composed of data scientists, front-end and back-end engineers, product managers, and analysts.
As an early team member, you'll have a unique opportunity to influence our technical direction and growth. Some travel may be required as we build our distributed team.
Core Skills;
- Strong track record of building and deploying ML systems in production, with hands-on experience in real-time, high-throughput environments.
- Strong foundation in applied ML frameworks and data science tools and libraries.
- Deep expertise in Python, with a focus on ML engineering best practices and production-grade code architecture.
- Experience with modern cloud platforms (AWS/GCP/Azure) and MLOps practices, including containerization and CI/CD for ML workflows.
- Practical exposure to modern cloud data platforms, with direct experience delivering data centric solutions for mission critical use cases; as well as driving innovation PoV style delivery and associated engineering/design principles.
- Experience in distributed microservice architecture and REST API development. Hands-on experience with streaming architectures and real-time processing systems.
- Track record of making architectural decisions that balance innovation with reliability.
- Demonstrated ability to work independently and drive technical initiatives from concept to production.
- Evidence of motivation to learn, and curiosity around modern approaches to ML engineering. Ability to discuss and debate relative merits and opportunities.
Desired
- Experience with LLMs and modern NLP techniques. Building and optimizing RAG systems, working with embedding models and vector stores.
- Background in scaling ML systems from prototype to production.
- Previous experience in a fast paced start-up environment.
- Understanding of ML monitoring and observability best practices.
This role isnt for a beginner, it is for someone who has the ability to solve problems, create solutions and really help a super exciting business become the next big rocket ship.
Apply with your most recent CV to be considered for shortlisting.
