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- Tasks: Join our AI team as an MLOps Engineer, enhancing ML infrastructure and deployment processes.
- Company: DigitalGenius is a cutting-edge AI company revolutionising E-Commerce customer service with deep learning.
- Benefits: Enjoy competitive salary, generous vacation, fitness stipend, and mental health support.
- Why this job: Be part of a dynamic team driving innovation in AI while developing your skills in a supportive environment.
- Qualifications: Degree in a relevant field with 3+ years experience; strong skills in Python, AWS, and Docker required.
- Other info: We value diversity and are committed to creating an inclusive workplace for all.
The predicted salary is between 43200 - 72000 £ per year.
Description
DigitalGenius (DG) is a venture-backed artificial intelligence company bringing practical applications of deep learning and AI to some of the largest E-Commerce customer service operations in the world as well as high-growth companies. Were a dedicated team of thoughtful and hard-working people committed to transforming customer service through the application of artificial intelligence.
Role
The continuous improvement of our products and the range of innovation projects we are committed to, require us to scale our Machine Learning team. We are searching for an MLOps Engineer to join our core AI Team. This is a highly technical role for an outstanding individual who can take ownership of projects and start new initiatives.
As an MLOps Engineer, you will be responsible for designing, deploying, and maintaining scalable infrastructure and processes that support our AI systems in production. Your time will be divided between improving our ML infrastructure, building deployment and monitoring systems, and working closely with our ML engineers and product teams. This is an excellent opportunity for those with strong Engineering and DevOps capabilities and a deep interest in operationalising AI solutions. We are looking for someone with complementary skills that extend into infrastructure and observability, preferably with experience in E-Commerce.
The AI team owns all ML-related research, implementation and maintenance. In practice, this means keeping up to date with best practices in production ML, developing and supporting scalable infrastructure, and enabling faster and safer experimentation and deployment.
Responsibilities
- Proactive approach with team members and clients
- Continuous improvement of ML infrastructure and operations
- Take ownership of the deployment and monitoring pipelines within your expertise
- Contribute to the ongoing innovation R&D projects by enabling production readiness
- Maintain and implement CI/CD pipelines, observability, and infrastructure for ML services
Requirements
- Degree in relevant field with 3+ years of industry experience
- Strong Technical Skills: Python, AWS, Docker, Terraform
- Experience deploying and maintaining machine learning models in production environments
- Familiarity with MLOps best practices: versioning, monitoring, model registries, CI/CD
- Excellent organisation skills, working independently and ability to deliver results for deadlines
- A proactive, innovative, pragmatic approach to problem-solving and an ability to think critically and objectively
- Good customer-facing skills and ability to communicate technical concepts to technical and non-technical audiences
- Experience in E-Commerce space
Benefits
- Competitive Salary
- Generous vacation time (25 days)
- Yearly DG Recharge Week in addition to annual leave allowance
- Freedom to experiment with your own ideas
- Environment to develop your skills without bureaucracy or red tape
- Monthly fitness stipend of $210 or fully paid Third Space Membership.
- On going subscription to Mental Health Support Platform
We are an equal-opportunity employer and value diversity at our company. We do not discriminate based on race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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Machine Learning Ops Engineer (London) employer: DigitalGenius
Contact Detail:
DigitalGenius Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Ops Engineer (London)
✨Tip Number 1
Familiarise yourself with the latest MLOps tools and practices. Since the role requires a strong understanding of CI/CD pipelines and model monitoring, being well-versed in these areas will help you stand out during discussions.
✨Tip Number 2
Network with professionals in the AI and E-Commerce sectors. Attend relevant meetups or webinars to connect with people who work at DigitalGenius or similar companies, as personal connections can often lead to job opportunities.
✨Tip Number 3
Showcase your hands-on experience with Python, AWS, Docker, and Terraform through personal projects or contributions to open-source. Having tangible examples of your work can make a significant impact during interviews.
✨Tip Number 4
Prepare to discuss how you've improved ML infrastructure in past roles. Be ready to share specific examples of challenges you've faced and how you overcame them, as this demonstrates your proactive approach and problem-solving skills.
We think you need these skills to ace Machine Learning Ops Engineer (London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in MLOps, particularly with technologies like Python, AWS, Docker, and Terraform. Emphasise any projects where you've deployed machine learning models in production.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and E-Commerce. Discuss how your skills align with the responsibilities of the role and provide examples of your proactive approach to problem-solving.
Showcase Your Technical Skills: Include specific examples of your technical skills in your application. Mention any experience with CI/CD pipelines, observability, and infrastructure for ML services, as these are crucial for the role.
Highlight Soft Skills: Don't forget to mention your organisational skills and ability to communicate complex concepts clearly. This is important for collaborating with both technical and non-technical team members.
How to prepare for a job interview at DigitalGenius
✨Showcase Your Technical Skills
Make sure to highlight your experience with Python, AWS, Docker, and Terraform during the interview. Be prepared to discuss specific projects where you've deployed and maintained machine learning models in production environments.
✨Demonstrate Your Problem-Solving Approach
Prepare examples that showcase your proactive and innovative problem-solving skills. Discuss how you've tackled challenges in previous roles, particularly in relation to improving ML infrastructure or operations.
✨Communicate Clearly
Since the role involves working with both technical and non-technical teams, practice explaining complex concepts in simple terms. This will demonstrate your ability to bridge the gap between different audiences.
✨Familiarise Yourself with MLOps Best Practices
Brush up on MLOps best practices such as versioning, monitoring, and CI/CD pipelines. Being able to discuss these topics confidently will show that you are well-prepared for the responsibilities of the role.
