At a Glance
- Tasks: Lead ML teams to solve real-world problems using Large Language Models.
- Company: Join a pioneering tech firm shaping the future of Enterprise AI.
- Benefits: Competitive salary, flexible work options, and opportunities for mentorship.
- Other info: Collaborative environment with chances for rapid career advancement.
- Why this job: Make a significant impact by disrupting industries with innovative AI solutions.
- Qualifications: Experience in ML, 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) in London 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) in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the ML space and let them know you're on the lookout for opportunities. Attend industry meetups or webinars to meet potential employers and showcase your passion for applied ML.
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your projects, especially those involving Python and ML frameworks. This will give you an edge when discussing your experience during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your problem-solving skills. Practice coding challenges and be ready to discuss your approach to building and refining ML products. We want to see how you think!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about joining our team.
We think you need these skills to ace Member of Technical Staff (Machine Learning Engineering, UK/EU) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your leadership in ML teams and any relevant projects you've worked on, especially those involving Python and ML frameworks.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about applied ML models and how your experience aligns with our mission. Share specific examples of how you've tackled challenges in previous roles.
Showcase Your Problem-Solving Skills:In your application, don’t just list your skills—demonstrate them! Describe situations where you’ve successfully solved complex problems or led projects from ideation to production.
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 your enthusiasm for joining our team!
How to prepare for a job interview at Cohere
✨Showcase Your Leadership Experience
Make sure to highlight your previous experience in leading ML teams. Prepare specific examples of how you set technical direction and executed projects, especially in cross-discipline environments. This will demonstrate your capability to mentor and guide a team effectively.
✨Demonstrate Technical Proficiency
Brush up on your Python skills and be ready to discuss your experience with ML frameworks like TensorFlow and JAX. You might even want to prepare a mini-project or case study that showcases your ability to apply these tools in real-world scenarios.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving abilities. Think of complex challenges you've tackled in the past, particularly those involving large-scale distributed training and inference. Be ready to walk through your thought process and the solutions you implemented.
✨Align with Company Goals
Research the company’s mission and recent projects. Be prepared to discuss how your skills and experiences align with their goals, especially in terms of Enterprise AI adoption. Showing that you understand their vision will set you apart as a candidate who is genuinely interested in contributing.
