At a Glance
- Tasks: Design and deploy cutting-edge AI and machine learning solutions using generative models.
- Company: Join a dynamic team focused on innovative AI applications across diverse industries.
- Benefits: Enjoy competitive salary, comprehensive benefits, and flexible working arrangements.
- Why this job: Work on impactful projects that drive real business outcomes and advance your expertise.
- Qualifications: 4+ years in AI/ML development, proficiency in Python, and experience with Databricks and cloud services.
- Other info: Collaborate with a passionate team of AI experts to tackle complex challenges.
The predicted salary is between 43200 - 72000 £ per year.
Job Title: AI Engineer (Generative AI & Machine Learning Specialist) Location: Manchester or London Employment Type: Full-time Experience Level: Mid to Senior About the Role As an AI Engineer , you will design, build, and deploy AI and machine learning solutions using generative models and advanced ML models and techniques. You will leverage Databricks to create scalable and efficient workflows while collaborating with clients and internal teams to deliver high-value solutions. This role combines technical expertise with creativity to develop next-generation AI applications for diverse industries. Key Responsibilities Generative AI Development: Design and fine-tune generative models (e.g., Llama 2, MPT, GPT, DALL-E, Stable Diffusion) for applications such as natural language processing, content creation, or synthetic data generation. Machine Learning: Build and deploy advanced machine learning models for tasks like classification, regression, recommendation systems, and anomaly detection. Platform Integration: Develop scalable ML pipelines on Databricks, utilizing tools like MLflow, Delta Lake, and Spark for end-to-end workflows. Solution Architecture: Collaborate with architects and engineers to design AI systems that address specific business needs and integrate seamlessly with existing infrastructures. Model Optimization: Optimize AI and ML models for performance, scalability, and cost efficiency, including distributed training on Databricks. Cloud Deployment: Leverage cloud services (Azure, AWS, GCP) to deploy, monitor, and manage AI and ML models in production. Innovation & Prototyping: Develop prototypes and proof-of-concept solutions using generative AI and ML to demonstrate value to clients. Required: 4+ years of experience in AI and machine learning development. Hands-on experience with Databricks and cloud-based AI/ML solutions (ML Flow, Mosaic AI). Proficiency in Python and machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn. Experience with generative models (e.g., LLM’s, Multi-Modal Models, VAEs, GANs) and their deployment. Strong knowledge of Databricks tools such as MLflow, Mosaic AI, Delta Lake, and Apache Spark. Deep understanding of machine learning algorithms, model training, and evaluation techniques. Experience with Azure (preferred), AWS, or GCP for model deployment and infrastructure management. Strong analytical and problem-solving skills. Excellent communication abilities for both technical and non-technical audiences. Experience with CI/CD for machine learning workflows and automated model deployment. Certifications in Databricks or cloud platforms (e.g., Azure AI Engineer Associate). Knowledge of real-time data processing and streaming applications. Familiarity with visualization tools like Power BI or Tableau. Experience applying AI solutions in industries such as healthcare, finance, or retail. Why Join Us? Impactful Projects: Work on innovative AI and ML solutions that drive measurable business outcomes for global clients. Growth Opportunities: Advance your expertise in generative AI, machine learning, and Databricks technologies. Innovative Team: Join a collaborative team of AI experts who are passionate about solving complex challenges. Competitive Benefits: Enjoy a competitive salary, comprehensive benefits, and flexible working arrangements.
Artificial Intelligence Engineer employer: NP Group
Contact Detail:
NP Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer
✨Tip Number 1
Familiarize yourself with the latest generative AI models like Llama 2 and DALL-E. Being able to discuss their applications and nuances in an interview will show your passion and expertise in the field.
✨Tip Number 2
Gain hands-on experience with Databricks, especially with tools like MLflow and Delta Lake. Consider working on personal projects or contributing to open-source projects that utilize these technologies to demonstrate your skills.
✨Tip Number 3
Network with professionals in the AI and machine learning community. Attend meetups, webinars, or conferences focused on generative AI and cloud deployment to make connections that could lead to job opportunities.
✨Tip Number 4
Prepare to discuss real-world applications of AI in industries like healthcare or finance. Having specific examples ready can help you illustrate your understanding of how AI solutions can drive business outcomes.
We think you need these skills to ace Artificial Intelligence Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI and machine learning development. Focus on your hands-on experience with Databricks, cloud services, and generative models, as these are key requirements for the role.
Craft a Strong Cover Letter: In your cover letter, express your passion for AI and machine learning. Mention specific projects or experiences that demonstrate your expertise in generative AI and your ability to collaborate with teams to deliver high-value solutions.
Showcase Technical Skills: Clearly outline your proficiency in Python and machine learning frameworks like TensorFlow and PyTorch. Include any certifications you have in Databricks or cloud platforms, as this will strengthen your application.
Highlight Problem-Solving Abilities: Provide examples of how you've tackled complex challenges in previous roles. Emphasize your analytical skills and your experience with CI/CD for machine learning workflows, as these are crucial for the position.
How to prepare for a job interview at NP Group
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with AI and machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn. Highlight specific projects where you designed and deployed generative models or advanced ML solutions.
✨Demonstrate Problem-Solving Abilities
Expect to face technical challenges during the interview. Use examples from your past work to illustrate how you approached complex problems, optimized models, or integrated AI systems into existing infrastructures.
✨Familiarize Yourself with Databricks
Since this role emphasizes the use of Databricks, make sure you understand its tools like MLflow, Delta Lake, and Spark. Be ready to discuss how you've utilized these tools in your previous projects to create scalable ML pipelines.
✨Communicate Effectively
You will need to convey complex technical concepts to both technical and non-technical audiences. Practice explaining your projects and methodologies clearly and concisely, focusing on the impact and value of your work.