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- Tasks: Join us to design and deploy cutting-edge AI/ML models for the rental housing market.
- Company: Letly is an innovative fintech platform revolutionising rental workflows with AI technology.
- Benefits: Enjoy competitive salary, equity options, and a meritocratic progression system.
- Why this job: Be part of a dynamic team tackling real-world challenges with AI in a high-impact role.
- Qualifications: Strong software engineering skills and experience with ML frameworks are essential.
- Other info: This is an entry-level full-time position based in London.
The predicted salary is between 28800 - 48000 £ per year.
Letly is an AI-Native vertical fintech platform focused on the rental housing market. We are automating rental workflows end-to-end and building a fintech platform underneath to manage the trillions of dollars spent on rent globally. We recently closed a pre-seed round and are hiring one talented AI/ML engineer with a strong software engineering background and a passion for deploying AI/ML models into real-world, production-grade applications.
Apply if:
- You have strong foundational software engineering knowledge, including data structures, algorithms, system design, and OOP.
- You have advanced knowledge of LLM architectures and ML/DL frameworks (e.g. TensorFlow, PyTorch, LangChain, Keras, scikit-learn).
- You’re ready to design, deploy and maintain production-grade Machine Learning systems.
- You’re willing to champion best practices in code quality, testing, observability and MLOps.
- You have experience with MLOps tools and practices (CI/CD, Docker, Kubernetes) and cloud platforms (GCP, AWS, or Azure).
- You’re a smart, intense, and focused individual willing to build things efficiently in a close team.
- You want to tackle large technical hurdles, and build first-of-its-kind software using AI.
You will:
- Write high-quality, maintainable, well-documented, and tested code, adhering to software engineering best practices.
- Design, implement, and deploy production-grade AI/ML models to address various platform needs (including NLP and OCR).
- Optimise AI models and associated systems for performance, scalability, and cost-effectiveness in a production environment.
- Implement and manage the infrastructure for MLOps, including fine-tuning, deployment, monitoring and versioning.
- Develop robust data pipelines for ingestion, cleaning, model training, and continuous deployment.
- Build retrieval-aware repositories for model training, evaluation, and real-time context-rich inference.
- Collaborate closely with the software engineers to integrate AI models seamlessly into the platform architecture using APIs.
- Be a key part of a high-performance, engineering and product-led company with a high degree of autonomy and impact.
Compensation:
- Competitive salary and meaningful equity in the company.
- Annual performance-based compensation (cash and equity).
- Opportunity for true meritocratic progression in role and compensation.
Stand-up the rule-evaluation core of the compliance microservice: JSONLogic/CEL engine to load rule set from Mongo and return pass/fail result. Wire a Pub/Sub sink to integrate with the rest of the system, emitting ComplianceDecision events, and land these in BigQuery for analytics. Light-up observability – deploy OpenTelemetry traces + Grafana dashboards, and config alerts for latency, failure %, override rate.
Seniority level: Entry level
Employment type: Full-time
Job function: Engineering and Information Technology
Industries: Software Development
Founding Machine Learning Engineer employer: Letly
Contact Detail:
Letly Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Founding Machine Learning Engineer
✨Tip Number 1
Familiarise yourself with the specific AI/ML frameworks mentioned in the job description, such as TensorFlow and PyTorch. Consider building a small project or contributing to an open-source one that showcases your skills in these areas.
✨Tip Number 2
Network with professionals in the fintech and AI sectors. Attend meetups or webinars where you can connect with people from Letly or similar companies. This could give you insights into their culture and expectations.
✨Tip Number 3
Prepare to discuss your experience with MLOps tools like Docker and Kubernetes. Be ready to share examples of how you've implemented CI/CD pipelines in past projects, as this is crucial for the role.
✨Tip Number 4
Showcase your problem-solving skills by preparing for technical interviews. Practice coding challenges that focus on data structures and algorithms, as these are fundamental to the software engineering aspect of the role.
We think you need these skills to ace Founding Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your software engineering skills, particularly in data structures, algorithms, and system design. Include specific projects or experiences that demonstrate your knowledge of ML/DL frameworks like TensorFlow or PyTorch.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and ML, and explain how your background aligns with the role at Letly. Mention any relevant experience with MLOps tools and cloud platforms, and how you can contribute to their mission.
Showcase Relevant Projects: If you have worked on any AI/ML projects, include them in your application. Describe your role, the technologies used, and the impact of the project. This will help demonstrate your practical experience and problem-solving skills.
Highlight Collaboration Skills: Letly values teamwork, so be sure to mention any collaborative projects you've been part of. Discuss how you’ve worked with others to integrate AI models into applications, as this shows your ability to work effectively in a team environment.
How to prepare for a job interview at Letly
✨Showcase Your Technical Skills
Be prepared to discuss your foundational software engineering knowledge, including data structures, algorithms, and system design. Highlight your experience with ML/DL frameworks like TensorFlow or PyTorch, and be ready to explain how you've deployed AI/ML models in real-world applications.
✨Demonstrate MLOps Knowledge
Since the role involves managing MLOps infrastructure, make sure to talk about your experience with CI/CD, Docker, and Kubernetes. Discuss any projects where you implemented these tools and how they improved your workflow.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving abilities. Practice coding challenges related to AI model optimisation and data pipeline development, as these are crucial for the role at Letly.
✨Emphasise Team Collaboration
Letly values teamwork, so share examples of how you've collaborated with software engineers or cross-functional teams. Discuss how you integrated AI models into existing systems and the impact it had on the project.
