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- Tasks: Join us as a Senior AI Engineer to build tools and optimize models in fintech.
- Company: We're an AI-driven SAAS company revolutionizing the fintech space.
- Benefits: Enjoy remote work flexibility and part-time hours while making an impact.
- Why this job: Work on cutting-edge AI projects with a focus on innovation and collaboration.
- Qualifications: 6+ years in AI Engineering, expertise in LLMs, NLP, and Python required.
- Other info: This role is part-time, 1-2 days a week, perfect for balancing studies or other commitments.
The predicted salary is between 60000 - 84000 £ per year.
Senior AI Engineer
⚡️ Fintech / Investments / SAAS
London (remote in EMEA)
Part time – 1-2 days per week over 4 months (during core UK work hours)
Minimum 6 years of relevant experience required
Candidates must be based in the EMEA region, be fluent in English with excellent communication skill and have their own device to perform the required work.
Our client, an AI-driven SAAS company in the fintech space, is seeking a Senior AI Engineer to assist in a key project on a part time basis over the next 5 months.
The following proven track record will aid you in achieving these deliverables over the term of engagement:
- Tool Development: Build a robust tool that integrates APIs from multiple providers
- Prompt Engineering: Design and test high-quality prompts to generate reports, ensuring they include detailed analyses of predetermined metrics.
- Data Integration: Process and combine structured and unstructured data sources
- Model Customization: Customize or fine-tune LLMs
- Output Optimization: Ensure generated reports are accurate, insightful, and adhere to high-quality standards for clarity and relevance.
- Scalability: Ensure the tool and models can handle increased data loads and user demands in the future.
- Documentation: Provide clear documentation of the system’s architecture, APIs used, prompt workflows, and data pipelines.
- Given the project requirements, you should have hands on commercial experience in:
- LLMs (Large Language Models): Fine-tuning or prompt engineering with GPT-based models for natural language generation and analysis.
- NLP: For text analysis and summarization, including techniques like sentiment analysis, named entity recognition (NER), and keyphrase extraction.
- Supervised Learning Models (as needed): To build complementary analytical insights, like regression or classification tasks based on structured data.
- Generative AI: Crafting high-quality prompts and leveraging GenAI for creating reports tailored to specific audiences.
- Potential exploration of unsupervised models (e.g., clustering or dimensionality reduction) if pattern recognition in unstructured data is required.
We are looking for a Senior AI Engineer with:
- Min 6 years hands on experience in an AI Engineering focus role (similar to the above)
- LLMs, NLP, Gen AI experience is required
- Programming & Scripting: Python (essential for integrating APIs and developing ML solutions)
- Machine Learning Libraries: TensorFlow or PyTorch (for model development and fine-tuning), Scikit-learn (for baseline supervised/unsupervised models).
- Data Manipulation & Visualization: Numpy, Pandas (data preprocessing and analysis), Matplotlib or Seaborn (visualizations for insights).
- Prompt Engineering & NLP Integration: OpenAI APIs or similar (for working with LLMs like GPT or Claude).
- Workflow & Collaboration: Git (version control), MLflow (experiment tracking), and ideally Airflow or Kubeflow (for orchestration).
- Optional but beneficial: Experience with cloud platforms like AWS, Azure, or GCP for deploying and scaling solutions.
Apply Now to be considered and we will endeavour to reach out to discuss the role and client in further detail should you be a suitable fit.
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Senior AI Engineer employer: Sataya
Contact Detail:
Sataya Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI Engineer
✨Tip Number 1
Make sure to showcase your hands-on experience with LLMs and NLP in your conversations. Highlight specific projects where you've fine-tuned models or engineered prompts, as this will resonate well with our client's needs.
✨Tip Number 2
Familiarize yourself with the latest trends in generative AI and be ready to discuss how you've applied these techniques in real-world scenarios. This will demonstrate your up-to-date knowledge and practical skills.
✨Tip Number 3
Prepare to talk about your experience with data integration and manipulation tools like Pandas and Numpy. Being able to explain how you've processed both structured and unstructured data will set you apart from other candidates.
✨Tip Number 4
Since this role involves collaboration, be ready to discuss your experience with version control systems like Git and orchestration tools like Airflow or Kubeflow. Emphasizing your teamwork skills will show that you're a great fit for the project.
We think you need these skills to ace Senior AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in AI engineering, particularly with LLMs, NLP, and Generative AI. Use specific examples that demonstrate your skills in tool development, prompt engineering, and data integration.
Craft a Strong Cover Letter: Write a cover letter that clearly outlines your motivation for applying to this role. Emphasize your hands-on experience and how it aligns with the project requirements. Mention your familiarity with the tools and technologies listed in the job description.
Showcase Your Projects: If applicable, include links or descriptions of past projects that showcase your expertise in building APIs, customizing models, and generating insightful reports. This will help demonstrate your practical knowledge and problem-solving abilities.
Proofread Your Application: Before submitting, carefully proofread your application materials to ensure there are no grammatical errors or typos. A polished application reflects your attention to detail and professionalism, which is crucial for a Senior AI Engineer role.
How to prepare for a job interview at Sataya
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with LLMs, NLP, and generative AI. Highlight specific projects where you've fine-tuned models or developed tools that integrate APIs, as this aligns closely with the job requirements.
✨Demonstrate Problem-Solving Abilities
Expect to face scenario-based questions that assess your ability to handle data integration and model customization. Use examples from your past work to illustrate how you approached challenges and optimized outputs.
✨Communicate Clearly and Effectively
Since excellent communication skills are a must, practice explaining complex technical concepts in simple terms. This will help demonstrate your ability to document systems and collaborate with team members.
✨Prepare for Behavioral Questions
Be ready to discuss your workflow and collaboration experiences, especially with tools like Git and MLflow. Share how you've worked in teams and contributed to project success, as this will show your fit for a part-time role in a collaborative environment.
