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For Companies At a Glance
- Tasks: Join a dynamic team to develop and optimize AI/ML models, focusing on generative AI and LLMs.
- Company: A pioneering AI-first SaaS company recently listed on NASDAQ, transforming commerce with cutting-edge technology.
- Benefits: Enjoy a competitive salary, pension, stock options, and free in-office lunches.
- Why this job: Be part of an innovative team shaping the future of AI in commerce while working in vibrant Piccadilly Circus.
- Qualifications: Experience in AI/ML engineering, strong Python skills, and familiarity with cloud services like AWS or Google Cloud.
- Other info: Non-UK citizens requiring sponsorship cannot apply; must have unrestricted work visa for at least 5 years.
The predicted salary is between 68000 - 102000 £ per year.
Job: AI/ML Engineer (London W1)
- Salary to £85k (Mid), to £120k (Senior)
- Benefits: pension, stock options*, free in-office lunches
- Location: Mon-Fri onsite in London W1 offices (Piccadilly Circus)
Company
Having recently floated on *NASDAQ, this company is a dynamic, AI-first SaaS company known for leveraging the latest advancements in Generative AI to deliver world-class AI commerce solutions. Recognized by industry leaders, they are in an exciting growth phase and seeking experienced professionals to join their innovative team. This is a chance to join a pioneering team that’s transforming the future of commerce with AI and ML!
Working Mon-Fri from their Piccadilly Circus offices, they are looking for AI/ML Engineers to join their growing development team. They are looking for skilled and confident individuals to join them in the delivery and success of their core platform and AI Vertical in Generative AI and Product Recommendations.
Role
As an AI/ML Engineer, you will be part of a dynamic engineering team dedicated to building AI/ML models, maintaining high-performance systems, and driving the development of scalable AI solutions. You will collaborate closely with cross-functional teams to deliver key AI-driven functionalities. This includes designing, implementing, and optimizing machine learning algorithms, particularly for Large Language Models (LLMs) and generative AI projects. You will also contribute to the continuous improvement of their AI platform and ensure the seamless integration of AI components into the larger ecosystem.
Responsibilities
- Develop, implement, and optimize AI/ML models with a focus on LLMs and generative AI.
- Collaborate with software engineers to integrate AI components into production systems.
- Design and maintain efficient machine learning pipelines for large-scale data processing.
- Work with cloud platforms (AWS, Google Cloud) to deploy and manage AI/ML solutions.
- Build and maintain RESTful APIs to enable AI services for various use cases.
- Engage in data preprocessing, cleansing, and feature engineering to ensure high-quality inputs for AI models.
- Conduct benchmarking and performance optimization to improve model accuracy and efficiency.
- Contribute to the entire software lifecycle, including requirement gathering, design, implementation, testing, and deployment.
- Stay updated with the latest AI/ML advancements and apply them to improve system performance and capabilities.
Required
- Experience in AI/ML engineering and Gen AI Building LLM from scratch.
- Strong expertise in Python and common AI/ML libraries (e.g., PyTorch, TensorFlow, Scikit-learn).
- Experience working with LLMs and understanding of transformer-based architectures.
- Familiarity with vector databases and experience with embeddings (e.g., for text or product recommendations).
- Proven experience with cloud services (AWS, Google Cloud) for deploying machine learning models.
- Hands-on experience with data processing and massaging techniques for AI/ML workflows.
- Knowledge of CI/CD pipelines, version control systems (GitHub), and containerization (Docker, Kubernetes).
- Excellent problem-solving skills and ability to troubleshoot complex AI/ML issues with deep learning, neural networks, and optimizers for fine-tuning.
Desirable
- Prior experience with fine-tuning LLMs or generative models for specific tasks.
- Knowledge of distributed systems and parallel processing for large-scale model training.
- Familiarity with additional tools like Kafka, RabbitMQ, or message queue systems.
- Exposure to various activation functions, loss functions, and neural network layers commonly used in deep learning.
Education
Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or a related field.
Other Stuff
NB: for non-UK Citizens: we cannot accept applications from anyone requiring sponsorship (now or in the future) for UK permanent employment status. If you are using a work visa this must allow you to work in the UK unrestricted for at least the next 5 years.
In accordance with GDPR by applying you give Profile 29 consent to use your data for recruitment purposes only (details of Profile 29’s privacy policy can be found at: profile-29.com/privacy)
Profile 29 recruitment keywords: artificial intelligence machine learning saas London google cloud aws large language models llm #J-18808-Ljbffr
AI/ML Engineer employer: Talkspirit
Contact Detail:
Talkspirit Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI/ML Engineer
✨Tip Number 1
Make sure to showcase your hands-on experience with AI/ML models, especially in building Large Language Models (LLMs). Highlight any specific projects where you've implemented generative AI solutions, as this will resonate well with the company's focus.
✨Tip Number 2
Familiarize yourself with the latest advancements in AI and ML technologies. Being able to discuss recent trends or breakthroughs during your interview can demonstrate your passion and commitment to the field, which is crucial for a role in a dynamic company like this.
✨Tip Number 3
Prepare to discuss your experience with cloud platforms such as AWS or Google Cloud. Be ready to explain how you've deployed and managed AI/ML solutions in these environments, as this is a key requirement for the position.
✨Tip Number 4
Engage with the AI/ML community by participating in forums or attending meetups. Networking with professionals in the field can provide valuable insights and potentially lead to referrals, increasing your chances of landing an interview with us.
We think you need these skills to ace AI/ML Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in AI/ML engineering, particularly with LLMs and generative AI. Use specific examples of projects you've worked on that demonstrate your skills in Python and relevant libraries.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention how your background aligns with their focus on AI commerce solutions and your experience with cloud platforms like AWS or Google Cloud.
Showcase Relevant Projects: Include a section in your application that showcases relevant projects or contributions to open-source AI/ML initiatives. Highlight any experience with building and fine-tuning LLMs or working with vector databases.
Highlight Continuous Learning: Mention any recent courses, certifications, or workshops you've attended related to AI/ML advancements. This shows your commitment to staying updated in a rapidly evolving field.
How to prepare for a job interview at Talkspirit
✨Showcase Your AI/ML Expertise
Be prepared to discuss your experience with AI/ML engineering, particularly in building Large Language Models (LLMs) from scratch. Highlight specific projects where you've implemented generative AI solutions and the impact they had.
✨Demonstrate Technical Proficiency
Make sure to brush up on your Python skills and familiarize yourself with libraries like PyTorch and TensorFlow. Be ready to answer technical questions or even solve coding challenges related to machine learning algorithms during the interview.
✨Understand the Company’s AI Vision
Research the company’s recent advancements in AI and how they leverage generative AI for commerce solutions. Being able to articulate how your skills align with their goals will show your genuine interest in the role.
✨Prepare for Collaborative Scenarios
Since the role involves working closely with cross-functional teams, be ready to discuss your experience in collaborative environments. Share examples of how you’ve successfully integrated AI components into production systems and worked with software engineers.
