At a Glance
- Tasks: Lead ML teams to solve real-world problems using Large Language Models.
- Company: Join a pioneering tech firm focused on applied machine learning.
- Benefits: Competitive salary, flexible work options, and opportunities for mentorship.
- Other info: Dynamic role with opportunities for innovation and career growth.
- Why this job: Make a significant impact in Enterprise AI and disrupt industries globally.
- Qualifications: Experience in ML leadership, Python proficiency, and strong problem-solving skills.
The predicted salary is between 60000 - 80000 £ per year.
Requirements
- Prior experience in leading ML teams in applied research and production
- Prior experience in setting as well as executing technical direction to build new or to refine existing products
- Prior experience in working cross-discipline in matrixed organizations
- Proficiency in Python and related ML frameworks such as Tensorflow, TF-Serving, JAX, and XLA/MLIR
- Experience using large-scale distributed training and inference
- Strong mentorship, communication, and problem-solving skills
- A demonstrated passion for applied ML models and products
- Bonus: experience working for B2B companies in the ML space
What the job involves
- As a Member of Technical Staff on our Applied ML team, you will work directly with customers to quickly understand their greatest problems and design and implement solutions using Large Language Models
- You’ll apply your problem-solving ability, creativity, and technical skills to close the last-mile gap in Enterprise AI adoption
- You’ll be able to deliver products like early startup CTOs/CEOs do and disrupt some of the most important industries and institutions globally!
- Plan and execute large-group projects that carry through from ideation to production
- Bring cross-functional alignment across engineering, product and other disciplines
- Mentor a distributed team of engineers in subject matter expertise
- Identify opportunities and gaps in existing models and strategize what to work on
- Work closely with product teams to develop solutions
- Engage in collaborations with our partner organizations
- Assist our legal teams with preparation of patents on developed IP
- Join us at a pivotal moment, shape what we build and wear multiple hats!
Member of Technical Staff (Machine Learning Engineering, UK/EU) employer: Cohere
As a leading innovator in the Machine Learning space, we pride ourselves on fostering a dynamic work culture that encourages creativity and collaboration. Our team members enjoy exceptional growth opportunities through mentorship and cross-functional projects, all while working in a vibrant UK/EU location that champions diversity and inclusion. Join us to make a meaningful impact in Enterprise AI adoption and be part of a company that values your contributions and supports your professional journey.
StudySmarter Expert Advice🤫
We think this is how you could land Member of Technical Staff (Machine Learning Engineering, UK/EU)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ML frameworks like TensorFlow or JAX. We want to see your problem-solving prowess in action, so make sure to highlight your best work!
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios related to ML engineering. We recommend doing mock interviews with friends or using online platforms to get comfortable discussing your experience and thought process.
✨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, we love seeing candidates who are genuinely interested in joining our team at StudySmarter!
We think you need these skills to ace Member of Technical Staff (Machine Learning Engineering, UK/EU)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in leading ML teams and executing technical direction. We want to see how your skills align with the role, so don’t be shy about showcasing your Python proficiency and any relevant frameworks you've worked with!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about applied ML models and how your past experiences have prepared you for this role. We love seeing creativity and problem-solving skills in action!
Showcase Your Projects:If you've worked on any projects that involved large-scale distributed training or inference, make sure to mention them! We’re keen to see examples of your work and how you’ve tackled real-world problems using ML.
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’re considered for the role. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Cohere
✨Know Your ML Stuff
Make sure you brush up on your machine learning knowledge, especially around the frameworks mentioned like TensorFlow and JAX. Be ready to discuss your past experiences leading ML teams and how you've tackled real-world problems using these technologies.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've identified gaps in existing models and strategised solutions. Think about times when you’ve had to think creatively to close the last-mile gap in AI adoption—this will really impress them!
✨Cross-Discipline Collaboration
Since the role involves working across various teams, be ready to talk about your experience in matrixed organisations. Highlight instances where you’ve successfully aligned different disciplines to achieve a common goal.
✨Mentorship Matters
They’re looking for someone with strong mentorship skills, so think about how you can demonstrate this. Share stories of how you’ve guided others in your team, helped them grow, or contributed to their success in technical projects.
