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- Tasks: Design and deploy deep learning models to tackle real-world challenges.
- Company: Join a forward-thinking team in the heart of London.
- Benefits: Enjoy flexible working, cutting-edge projects, and a collaborative vibe.
- Why this job: Make an impact in AI while working with the latest technologies.
- Qualifications: Experience in deep learning and proficiency in Python required.
- Other info: Great opportunity for growth in a dynamic environment.
The predicted salary is between 36000 - 60000 £ per year.
Job Title: Contract Deep Learning Engineer
Location: London (Hybrid or On-site)
Contract Type: 6–12 months (with potential extension)
About the Role:
We are seeking a highly skilled Deep Learning Engineer to join our team on a contract basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis.
Key Responsibilities:
- Design and implement deep learning models using frameworks such as PyTorch or TensorFlow.
- Collaborate with data scientists, ML engineers, and product teams to define model requirements and deployment strategies.
- Optimize model performance and scalability for production environments.
- Conduct experiments, evaluate model performance, and iterate based on results.
- Maintain clear documentation and contribute to knowledge sharing across the team.
- Stay up-to-date with the latest research and techniques in deep learning.
Required Skills & Experience:
- Proven experience in developing and deploying deep learning models in production.
- Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras).
- Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow).
- Strong problem-solving skills and ability to work independently in a fast-paced environment.
Preferred Qualifications:
- MSc or PhD in Computer Science, Machine Learning, or related field.
- Experience with large-scale datasets and distributed training.
- Knowledge of model interpretability and responsible AI practices.
Benefits:
- Flexible working arrangements (hybrid or remote options available).
- Opportunity to work on cutting-edge AI projects.
- Collaborative and innovative team environment.
Deep Learning Engineer employer: Experis UK
Contact Detail:
Experis UK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Deep Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and deep learning space. Attend meetups, webinars, or conferences to meet potential employers and showcase your skills. Remember, sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your projects! Create a portfolio that highlights your deep learning models and any relevant work you've done. Use platforms like GitHub to share your code and document your thought process. This gives employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and deep learning concepts. Practice common interview questions and coding challenges related to Python and frameworks like PyTorch or TensorFlow. The more prepared you are, the more confident you'll feel!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented Deep Learning Engineers like you. Keep an eye on our listings and make sure your application stands out by tailoring it to each role.
We think you need these skills to ace Deep Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with deep learning models and relevant frameworks like PyTorch or TensorFlow. We want to see how your skills match the job description, so don’t be shy about showcasing your projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about deep learning and how your background makes you a perfect fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects: If you've worked on any cool deep learning projects, make sure to mention them in your application. Whether it's a personal project or something from your previous job, we want to know what you've done and how it relates to the role.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at Experis UK
✨Know Your Frameworks
Make sure you brush up on your knowledge of deep learning frameworks like PyTorch and TensorFlow. Be ready to discuss your experience with these tools, including specific projects where you've implemented them. This will show that you're not just familiar with the theory but have practical skills to back it up.
✨Showcase Your Problem-Solving Skills
Prepare to talk about complex problems you've solved using deep learning. Think of specific examples where you designed and deployed models, and be ready to explain your thought process. This will demonstrate your ability to tackle real-world challenges effectively.
✨Collaborate and Communicate
Since collaboration is key in this role, think of instances where you've worked with data scientists or product teams. Highlight how you defined model requirements and contributed to deployment strategies. Good communication skills can set you apart from other candidates.
✨Stay Current with Trends
Deep learning is a rapidly evolving field, so be prepared to discuss recent advancements or research that excites you. Showing that you're proactive about staying updated will reflect your passion for the field and your commitment to continuous learning.
