Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop data pipelines and lead ML projects from start to finish.
- Company: Join a dynamic team focused on innovative machine learning solutions.
- Benefits: Enjoy remote work, competitive salary, bonuses, and great perks.
- Why this job: Make an impact in ML while mentoring others and enhancing your skills.
- Qualifications: Need hands-on experience in ML, Python, SQL, and cloud technologies.
- Other info: Occasional trips to London may be required.
The predicted salary is between 80000 - 95000 £ per year.
Join to apply for the ML Engineer / Senior Machine Learning Engineer remote role at MYO .
Salary: £80,000 – £95,000 + 15% bonus + benefits.
Location: Remote / Home based (may require occasional trips to London).
This is a permanent role.
You will be responsible for developing data pipelines, taking data science prototype models to production, fixing production bugs, monitoring operations, and provisioning the necessary infrastructure in Azure.
Experience
- Hands-on industry experience in some combination of Software Engineering, ML Engineering, Data Science, DevOps, and Cloud Infrastructure work.
- Expertise in Python including experience in libraries such as Pandas and scikit-learn.
- High proficiency in SQL.
- Experience with the following technologies: Python ecosystem, Azure (VMs, Web Apps, Managed Databases), GitHub Actions, Terraform, Packer, Airflow, Docker, Kubernetes, Linux/Windows VM administration, Shell scripting (primarily Bash but PowerShell).
- A solid understanding of modern security and networking principles and standards.
- Bachelor’s or higher degree in Computer Science, Data Science, or a related quantitative degree from an accredited institution.
Accountabilities Will Include
- Leading Machine Learning projects end-to-end.
- Developing platform tooling (e.g., internal conda library, CLI tool for project setup, and provisioning infrastructure) for the Data Science team.
- Working with data scientists to understand their data needs and creating data pipelines to ingest data.
- Assisting data scientists in taking data science model prototypes to production.
- Mentoring and training junior team members.
- Collaborating with internal IT teams (security, Cloud, Global Active Directory, Architecture, Networking, etc.) to advance the team’s projects.
- Enhancing code deployment lifecycle.
- Improving model monitoring frameworks.
- Refining project operations documentation.
- Designing, provisioning, and maintaining the cloud infrastructure needed to support Data Engineering, Data Science, Machine Learning Engineers, and Machine Learning Operations.
- Writing high-quality code with high test coverage.
- Participating in code reviews to help improve code quality.
Technologies/Tools
Python, Azure (Virtual Machines, Azure Web Apps, Cloud Storage, Azure ML), Anaconda packages, Git, GitHub, GitHub Actions, Terraform, SQL, Artifactory, Airflow, Docker, Kubernetes, Linux/Windows VMs.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Information Technology
Industries
Software Development
#J-18808-Ljbffr
ML Engineer / Senior Machine Learning Engineer remote employer: MYO
Contact Detail:
MYO Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer / Senior Machine Learning Engineer remote
✨Tip Number 1
Make sure to showcase your hands-on experience with the technologies listed in the job description, especially Python and Azure. Highlight specific projects where you've developed data pipelines or deployed machine learning models to production.
✨Tip Number 2
Emphasize your ability to lead projects and mentor junior team members. Share examples of how you've successfully guided teams through the end-to-end process of machine learning projects.
✨Tip Number 3
Familiarize yourself with the tools mentioned, such as Docker, Kubernetes, and Terraform. If you have experience with these, be ready to discuss how you've used them to enhance code deployment and infrastructure management.
✨Tip Number 4
Prepare to discuss your understanding of modern security and networking principles, as this is crucial for the role. Think of scenarios where you've implemented security measures in your previous projects.
We think you need these skills to ace ML Engineer / Senior Machine Learning Engineer remote
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in ML Engineering, Software Engineering, and Data Science. Emphasize your hands-on experience with Python, SQL, and cloud technologies like Azure.
Craft a Strong Cover Letter: In your cover letter, express your passion for machine learning and data science. Mention specific projects where you led ML initiatives or developed data pipelines, showcasing your leadership skills.
Showcase Technical Skills: Clearly list your technical skills related to the job description, such as proficiency in Python libraries, familiarity with Azure, and experience with tools like Docker and Kubernetes. Provide examples of how you've used these technologies in past roles.
Prepare for Technical Questions: Be ready to discuss your technical expertise during interviews. Prepare to explain your experience with code deployment, model monitoring, and mentoring junior team members, as these are key responsibilities of the role.
How to prepare for a job interview at MYO
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with Python, SQL, and cloud technologies like Azure. Highlight specific projects where you've developed data pipelines or deployed machine learning models.
✨Demonstrate Leadership Experience
Since the role involves leading ML projects and mentoring junior team members, share examples of how you've successfully led teams or projects in the past. This will show your capability to take charge and guide others.
✨Prepare for Problem-Solving Questions
Expect questions that assess your ability to troubleshoot production bugs and enhance code deployment lifecycles. Think of scenarios where you resolved issues effectively and be ready to explain your thought process.
✨Understand the Company Culture
Research the company's values and work culture. Be ready to discuss how your personal values align with theirs, especially regarding collaboration with IT teams and enhancing project operations documentation.
