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- Tasks: Lead innovative ML projects and mentor junior engineers in a collaborative setting.
- Company: Global leader in languages and translation with a focus on cutting-edge technology.
- Benefits: Remote work across Europe, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact in the ML field while working with advanced technologies.
- Qualifications: Extensive experience in Python, TensorFlow, PyTorch, and a strong grasp of NLPs and LLMs.
- Other info: Join a dynamic team dedicated to pushing the boundaries of machine learning.
The predicted salary is between 43200 - 72000 £ per year.
A global languages and translation company is seeking a Staff/Lead Machine Learning Engineer to oversee technical projects, mentor junior team members, and architect cutting-edge machine learning solutions.
Ideal candidates will have extensive experience in Python, TensorFlow, PyTorch, and Scikit-learn, with a deep understanding of NLPs and LLMs.
This role is remote across Europe, offering the chance to lead innovative ML initiatives in a collaborative environment.
Remote Europe: Lead ML Engineer - LLMs & NLP employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Remote Europe: Lead ML Engineer - LLMs & NLP
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or join relevant online communities. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, TensorFlow, and NLP. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex ML concepts in simple terms, as you'll likely need to mentor others in the role.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications come directly from passionate candidates like you. Plus, it shows you're genuinely interested in joining our team.
We think you need these skills to ace Remote Europe: Lead ML Engineer - LLMs & NLP
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with Python, TensorFlow, PyTorch, and Scikit-learn in your application. We want to see how you've used these tools in real projects, especially in the realms of NLPs and LLMs.
Be a Team Player: Since this role involves mentoring junior team members, share examples of how you've collaborated with others in the past. We love seeing candidates who can lead and inspire their teammates!
Tailor Your Application: Don’t just send a generic CV and cover letter. Take the time to tailor your application to our job description. We appreciate when candidates show they understand what we’re looking for and how they fit into our vision.
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 this exciting opportunity in our innovative ML team!
How to prepare for a job interview at Harnham
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python, TensorFlow, PyTorch, and Scikit-learn. Brush up on your knowledge of NLPs and LLMs, as you’ll likely be asked to discuss specific projects or challenges you've faced using these technologies.
✨Showcase Your Leadership Skills
Since this role involves mentoring junior team members, be prepared to share examples of how you've successfully led teams or projects in the past. Highlight your approach to guiding others and fostering a collaborative environment.
✨Prepare for Technical Questions
Expect in-depth technical questions that assess your problem-solving skills and understanding of machine learning concepts. Practise explaining complex ideas clearly and concisely, as communication is key in a remote setting.
✨Ask Insightful Questions
Demonstrate your interest in the company and the role by preparing thoughtful questions. Inquire about their current ML initiatives, team dynamics, and how they envision the future of NLP and LLMs within the organisation.
