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- Tasks: Assist in designing and developing machine learning processes for various clients.
- Company: Data Reply is a leading data specialist offering innovative AI and ML solutions.
- Benefits: Enjoy extensive training, hackathons, and a vibrant work environment with peers who share your passion.
- Why this job: Work on exciting projects with top brands while growing your skills in a supportive culture.
- Qualifications: A minimum 2.1 degree in Engineering/Computer Science; experience in ML model deployment preferred.
- Other info: Flexible travel opportunities and a commitment to diversity in the workplace.
The predicted salary is between 28800 - 48000 £ per year.
Career Opportunities: Graduate AI and Machine LearningEngineer – (10783)
Requisition ID10783-Posted – Years of Experience (1) –Technology– Where (1) –Job
DATA REPLY are data specialists, offering data platforms, BI, advanced analytics and AI/Machine Learning (ML) solutions to drive business success. We specialise in developing, deploying and operating production data solutions on AWS cloud.www.data.reply.com
Role overview:
As a Graduate AI & Machine Learning Engineer, you\’ll assist our team inthe design and development of machine learningprocesses in a variety of client environments. You will support the analysis of client requirements and help generate suitable recommendations. You will help managethe ML lifecycle fromdata selection and collection, ML model design and creation all the way through tooperationalizationand monitoring. You will work closely with data scientists and senior MLOps Engineers to understand and implement models into production. At Data Reply, you\’ll enjoy extensive training opportunities coupled with a detailed learning pathto guide you along the way.You\’ll thrive in our diverse and vibrant work environment andwill be surrounded bypeerswho share your passion fordata and technology. As a graduate at Reply, you will get involved inHackathons, Code Challenges or Labcamps as well as our graduate learning programme. As a Data Reply consultant, you will love the opportunity to work on projects with some of the world’s leading brands.
Responsibilities:
Work closely with the Data Science team to introduce automation and governance in their machine learning pipelines
Manage the infrastructure and orchestration pipelines needed to automatically train and bring machine learning models to production
Implement solutions to monitorthe performance of Machine Learning models in production over time
Work in teams with other technical experts, e.g. Data Engineers, Data scientists, MLOps Engineers, Data Visualization Specialists
Interact with domain experts from different industries to understand and tackle challenging problems
Explore and understand client datain relation to the problem you’re tackling andcommunicate findings to clients and stakeholders
About the candidate:
A minimum 2.1 Bachelor’s degree in Engineering/Computer Science is required. The ideal candidatewill have a Bachelor’s degree in Engineering/Computer Science and a Master’s degree in Data Science or Artificial Intelligence
Excellent communications skills; an ability to communicate with impact, ensuring complex information is articulated in a meaningful way to wide and varied audiences
You have an excellent understanding of key concepts in computer science (e.g. databases, software engineering practices, cloud computing – especially AWS) and data science (e.g. machine learning process)
Excellent knowledge of Python includingPytorch, Tensorflow andSKLearn as well as initial knowledge of LangChain andRAGAS.
Familiarity with CI/CD workflows is required and experience with containerisation and deployment using Docker/Kubernetes will be considered a plus
1+ year experience working in relevant role (training, evaluating and deploying Machine learning model)
You can demonstrate a growth mindset in terms ofpicking up new challenges and transforming them in an opportunity to learn
Flexibility regarding business travelling and positiveattitude towards working across different client projects
Reply is an Equal Opportunities Employer and committed to embracing diversity in the workplace. We provide equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type regardless of age, sexual orientation, gender, identity, pregnancy, religion, nationality, ethnic origin, disability, medical history, skin colour, marital status or parental status or any other characteristic protected by the Law.
Reply is committed to making sure that our selection methods are fair to everyone. To help you during the recruitment process, please let us know of any Reasonable Adjustments you may need.
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GRADUATE AI AND MACHINE LEARNING ENGINEER employer: Reply, Inc.
Contact Detail:
Reply, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land GRADUATE AI AND MACHINE LEARNING ENGINEER
✨Tip Number 1
Familiarise yourself with the latest trends in AI and machine learning. Follow industry leaders on social media, read relevant blogs, and participate in online forums to stay updated. This knowledge will help you engage in meaningful conversations during interviews.
✨Tip Number 2
Build a portfolio showcasing your projects related to machine learning and AI. Include any hackathons, code challenges, or personal projects that demonstrate your skills in Python, TensorFlow, or PyTorch. A strong portfolio can set you apart from other candidates.
✨Tip Number 3
Network with professionals in the field by attending meetups, webinars, or conferences focused on AI and machine learning. Making connections can lead to valuable insights and potential job referrals, so don’t hesitate to reach out to others in the industry.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and understanding the machine learning lifecycle. Use platforms like LeetCode or HackerRank to sharpen your skills, and be ready to discuss your approach to problem-solving during the interview.
We think you need these skills to ace GRADUATE AI AND MACHINE LEARNING ENGINEER
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant skills and experiences related to AI and machine learning. Emphasise your knowledge of Python, machine learning frameworks like PyTorch and TensorFlow, and any experience with AWS.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and machine learning. Mention specific projects or experiences that demonstrate your ability to work in a team and tackle complex problems.
Showcase Relevant Projects: If you have worked on any projects related to machine learning or data science, include them in your application. Describe your role, the technologies used, and the outcomes achieved to illustrate your hands-on experience.
Highlight Soft Skills: In addition to technical skills, emphasise your communication abilities and flexibility. Mention how you can articulate complex information clearly and your willingness to adapt to different client projects.
How to prepare for a job interview at Reply, Inc.
✨Showcase Your Technical Skills
Make sure to highlight your knowledge of Python, especially libraries like PyTorch, TensorFlow, and Scikit-learn. Be prepared to discuss any projects or experiences where you've applied these skills, as well as your understanding of CI/CD workflows and containerisation.
✨Demonstrate Your Problem-Solving Ability
Prepare to discuss specific challenges you've faced in previous roles or projects related to machine learning. Explain how you approached these problems, the solutions you implemented, and the outcomes. This will show your analytical thinking and ability to tackle complex issues.
✨Communicate Effectively
Since excellent communication skills are essential for this role, practice articulating complex technical concepts in a clear and concise manner. Think about how you would explain your work to someone without a technical background, as you'll need to communicate findings to clients and stakeholders.
✨Emphasise Your Growth Mindset
Be ready to discuss how you've embraced new challenges in your career. Share examples of how you've learned from past experiences and adapted to new technologies or methodologies. This will demonstrate your willingness to grow and evolve in the fast-paced field of AI and machine learning.
