Machine Learning Engineering Manager

Machine Learning Engineering Manager

Full-Time 80000 - 100000 £ / year (est.) Home office (partial)
HyperScience

At a Glance

  • Tasks: Lead a team to develop innovative machine learning solutions for business automation.
  • Company: Join a forward-thinking tech company focused on impactful ML products.
  • Benefits: Enjoy top-notch healthcare, flexible PTO, stock options, and a pension match.
  • Other info: Collaborative environment with opportunities for personal and professional growth.
  • Why this job: Make a real difference by bridging ML technology with customer needs.
  • Qualifications: 3+ years in ML product development and 1+ year in leadership roles.

The predicted salary is between 80000 - 100000 £ per year.

We are looking for a technical manager with a passion for working on business-facing automation products to lead our Application Machine Learning team. The ideal candidate will be able to leverage a strong ML background to bridge the gap between the latest ML technologies and customer needs. This is a crucial role in the engineering department, with a significant contribution to the company's future. You will have a chance to work across the complete machine learning lifecycle, including data collection/generation, annotation, model building, training, testing, and releasing. While partnering with multiple product engineering teams, you will deliver a combination of end-to-end automation solutions and simple, reusable abstractions for complex machine learning tasks to back offices worldwide.

We are looking for an engineering leader with a blend of technical and people skills. You will be expected to get into the technical details of projects within your team while also understanding how to work cross-functionally to deliver the maximum value to our end users.

Responsibilities
  • Manage and guide a large team of Machine Learning engineers helping to set priorities and tasks.
  • Plan and manage multiple projects to ensure successful delivery.
  • Wrap ML modules in reusable application components, which can be integrated into different configurations depending on the specific customer’s needs.
  • Leverage your systems knowledge to deliver fast and scalable software, starting from the design of the system through development and extension.
  • Creatively solve problems even when the initial answer is unclear.
  • Actively participate in discussions and give ideas/guidance.
  • Assess where the optimization efforts should go in order to utilize better the ML components and know-how of the company.
Qualifications
  • 3+ years of industry experience using data-driven approaches to solve real-world problems through building an ML-related product from end-to-end, including data collection, modeling training, experiment, and release.
  • 1+ year(s) leadership experience as an engineering manager or technical lead for a group of engineers or data scientists - coaching, road mapping, and project management.
  • Expertise in machine learning for deep learning, and content understanding technologies, especially in NLP or CV-related areas.
  • Extensive experience building scalable machine learning systems and data-driven products working with cross-functional teams.
  • Well-developed software engineering fundamentals and the ability to write production code when needed.
  • Good communication skills and the ability to understand and synthesize requirements across multiple project domains.
  • Works effectively with cross-functional teams to build a trusted partnership.
  • Able to perform applied research projects and bring them to production.
  • Strong experience with one or more general-purpose languages (Java, C/C++, Python, etc).
Benefits & Perks
  • Top-notch healthcare for you and your family.
  • A pension match for up to 6% of your annual salary.
  • Flexible PTO with the approval of your manager.
  • 12 weeks of parental leave and an additional 4 weeks for birthing parents.
  • Stock options.

We are an equal opportunity employer. We welcome people of different backgrounds, experiences, abilities and perspectives. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.

Machine Learning Engineering Manager employer: HyperScience

Join a forward-thinking company that values innovation and collaboration, where as a Machine Learning Engineering Manager, you will lead a talented team in developing cutting-edge automation products. With a strong emphasis on employee growth, we offer top-notch healthcare, flexible PTO, and generous parental leave, all within a supportive work culture that encourages diverse perspectives and creative problem-solving. This role not only allows you to make a significant impact on our engineering department but also provides opportunities to work cross-functionally, ensuring your contributions are recognised and valued.

HyperScience

Contact Details:

HyperScience Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Machine Learning Engineering Manager

Tip Number 1

Network like a pro! Reach out to your connections in the machine learning field and let them know you're on the lookout for opportunities. You never know who might have the inside scoop on a role that’s perfect for you.

Tip Number 2

Show off your skills! Create a portfolio showcasing your machine learning projects, especially those that highlight your leadership and technical abilities. This will give potential employers a taste of what you can bring to the table.

Tip Number 3

Prepare for interviews by brushing up on both technical and managerial questions. Be ready to discuss how you've led teams and tackled complex ML problems. We want to see your passion and expertise shine through!

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at StudySmarter.

We think you need these skills to ace Machine Learning Engineering Manager

Machine Learning
Deep Learning
Natural Language Processing (NLP)
Computer Vision (CV)
Data Collection
Model Training
Project Management

Some tips for your application 🫡

Show Your Passion for ML:When writing your application, let your enthusiasm for machine learning shine through! We want to see how your passion aligns with our mission to create innovative automation products that meet customer needs.

Highlight Your Leadership Experience:Make sure to emphasise your experience in leading teams and managing projects. We’re looking for someone who can guide a large team of engineers, so share examples of how you've successfully coached and motivated others.

Be Specific About Your Skills:Don’t just list your skills; provide concrete examples of how you’ve applied them in real-world scenarios. Whether it’s building scalable ML systems or working with cross-functional teams, we want to know how you’ve made an impact.

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 don’t miss out on any important updates during the process!

How to prepare for a job interview at HyperScience

Know Your ML Stuff

Make sure you brush up on your machine learning knowledge, especially in areas like NLP and CV. Be ready to discuss specific projects you've worked on, the challenges you faced, and how you overcame them. This will show that you not only understand the theory but can also apply it practically.

Show Your Leadership Skills

As a Machine Learning Engineering Manager, you'll need to demonstrate your leadership experience. Prepare examples of how you've managed teams, set priorities, and guided projects to success. Highlight your ability to coach engineers and foster collaboration across different teams.

Communicate Clearly

Good communication is key in this role. Practice explaining complex technical concepts in simple terms. You might be asked to synthesise requirements from various stakeholders, so being able to articulate your thoughts clearly will be crucial during the interview.

Think Cross-Functionally

Be prepared to discuss how you would work with cross-functional teams to deliver value. Think about past experiences where you collaborated with product engineering or other departments. Show that you can bridge the gap between technical details and customer needs effectively.