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For Companies At a Glance
- Tasks: Design and deploy advanced AI models while collaborating with diverse teams.
- Company: Join a cutting-edge team leading the way in intelligent technology and digital transformation.
- Benefits: Enjoy hybrid or remote work options and a dynamic, innovative work environment.
- Why this job: Make a real impact by developing scalable AI solutions in high-impact settings.
- Qualifications: Strong AI/ML knowledge, Python skills, and experience with ML libraries required.
- Other info: Nice to have experience with edge computing and real-time data processing.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking a talented AI/ML Engineer to join a cutting-edge team at the forefront of intelligent technology and digital transformation. This role offers a unique opportunity to develop and deploy advanced AI models in high-impact environments.
What You'll Be Doing
- Designing, developing, and training neural networks to meet complex functional requirements.
- Deploying AI models efficiently on scalable server-based platforms.
- Collaborating with cross-functional teams to integrate ML capabilities into digital applications.
- Continuously improving model performance and infrastructure through experimentation and optimisation.
What We're Looking For
- Strong understanding of AI/ML fundamentals, including neural networks and deep learning architectures.
- Proficiency in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Experience deploying machine learning models in production environments.
- Familiarity with cloud-based platforms (e.g., AWS, Azure, GCP) and containerization tools (e.g., Docker, Kubernetes).
- A passion for building scalable and impactful AI solutions.
Nice to Have
- Experience working with edge computing or low-latency AI systems.
- Knowledge of data engineering pipelines and real-time data processing.
Machine Learning Engineer (hybrid or remote) employer: Explore Group
Contact Detail:
Explore Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (hybrid or remote)
✨Tip Number 1
Network with professionals in the AI/ML field. Attend meetups, webinars, or conferences to connect with others who work in similar roles. This can lead to valuable insights and potential referrals for positions like the one we have at StudySmarter.
✨Tip Number 2
Showcase your projects on platforms like GitHub. Having a portfolio of your work, especially projects that involve neural networks or deploying models, can significantly boost your visibility and demonstrate your skills to us.
✨Tip Number 3
Stay updated with the latest trends in AI and machine learning. Follow relevant blogs, podcasts, and research papers. Being knowledgeable about current advancements can help you stand out during interviews and discussions with our team.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and system design problems related to AI/ML. Familiarise yourself with common algorithms and frameworks we use, as this will help you feel more confident when discussing your expertise with us.
We think you need these skills to ace Machine Learning Engineer (hybrid or remote)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AI/ML fundamentals, neural networks, and deep learning architectures. Include specific projects where you've used Python and ML libraries like TensorFlow or PyTorch.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI solutions and how your skills align with the company's goals. Mention any relevant experience deploying machine learning models in production environments.
Showcase Relevant Projects: If you have worked on projects involving cloud platforms or containerization tools, be sure to include these in your application. Highlight any experience with AWS, Azure, GCP, Docker, or Kubernetes.
Proofread and Edit: Before submitting your application, carefully proofread your documents for any spelling or grammatical errors. A polished application reflects your attention to detail and professionalism.
How to prepare for a job interview at Explore Group
✨Showcase Your Technical Skills
Be prepared to discuss your experience with AI/ML fundamentals, particularly neural networks and deep learning architectures. Bring examples of projects where you've used Python and ML libraries like TensorFlow or PyTorch, as this will demonstrate your hands-on expertise.
✨Demonstrate Problem-Solving Abilities
During the interview, expect to face technical challenges or case studies. Approach these problems methodically, explaining your thought process clearly. This will show your ability to tackle complex functional requirements effectively.
✨Highlight Collaboration Experience
Since the role involves working with cross-functional teams, share specific instances where you've collaborated with others to integrate ML capabilities into applications. This will illustrate your teamwork skills and adaptability in a dynamic environment.
✨Discuss Continuous Improvement
Talk about how you have previously improved model performance through experimentation and optimisation. Providing concrete examples of how you've iterated on your work will reflect your commitment to excellence and innovation in AI solutions.
