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- Tasks: Create synthetic datasets and train advanced AI models to redefine industries.
- Company: Join a stealth-mode startup backed by top VCs, revolutionizing AI accessibility.
- Benefits: Enjoy a competitive salary, hybrid work model, and career growth opportunities.
- Why this job: Be at the forefront of AI innovation in a collaborative and dynamic environment.
- Qualifications: 3+ years of ML experience, strong Python skills, and familiarity with LLMs preferred.
- Other info: Shape the future of AI while working with an elite team of pioneers.
The predicted salary is between 72000 - 108000 £ per year.
Machine Learning Engineer (Up to £150K) – Top VC-Backed Stealth Startup London (Hybrid working) Are you ready to drive the next big leap in AI? We’re working with a stealth-mode startup—backed by top venture capitalists—on a mission to make AI more accessible than ever. Their groundbreaking solutions are redefining how industries leverage intelligent systems, accelerating innovation, and unlocking new possibilities in the data-driven world. If you thrive on ambitious challenges, love pushing boundaries, and are excited to work at the forefront of AI innovation, read on! What You’ll Do Generate & Curate Synthetic Data: Create large-scale synthetic datasets to power advanced AI models. Model Training & Evaluation: Train and experiment with state-of-the-art models, assessing data quality to maximize performance. Instruction Tuning & Alignment: Refine model instructions, optimize preference alignment, and keep AI systems ahead of the curve. Data-Focused Research: Lead initiatives to enhance data quality, improve model outcomes, and push the boundaries of AI development. Collaborate & Innovate: Work cross-functionally in a fast-paced environment where your ideas can shape the future of AI. What We’re Looking For Seasoned ML Expertise: 3+ years of hands-on machine learning experience, with a track record of executing end-to-end ML projects. Deep Tech Know-How: Strong background in ML, Deep Learning, LLMs, and frameworks like PyTorch. Python Proficiency: Bonus points for advanced Python skills. Synthetic Data & LLM Chops: Familiarity with synthetic data generation or large-scale LLM training is a plus. GPU-Based Training Skills (nice to have): Comfortable spinning up GPU training environments (e.g., Lambda, Runpod, SageMaker). Team Player: Thrives in a collaborative environment and loves to share knowledge and ideas. Why You’ll Love It High-Impact Role: Shape the future of AI at a top VC-backed startup poised for rapid growth. Competitive Salary: £90k to £150K plus benefits. Flexible Working: Enjoy a hybrid model – 3 days in the London office, 2 days WFH. Career Growth: Advance your skills alongside an elite team of AI pioneers. Cutting-Edge Tech: Access the latest AI innovations and help define new industry standards. Join a culture that values ingenuity, thrives on collaboration, and celebrates breakthroughs. If you’re eager to push AI to new frontiers, this is your opportunity to make a lasting impact. Send us your CV and let’s talk about how you can lead this AI revolution.
Machine Learning Engineer employer: Ethiq
Contact Detail:
Ethiq Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Familiarize yourself with the latest advancements in AI and machine learning. Stay updated on trends, especially in synthetic data generation and large-scale LLM training, as this knowledge will help you stand out during discussions.
✨Tip Number 2
Engage with the AI community through forums, webinars, or local meetups. Networking with professionals in the field can provide insights into the startup culture and may even lead to referrals.
✨Tip Number 3
Prepare to discuss your past projects in detail, particularly those that involved end-to-end machine learning processes. Highlight your experience with frameworks like PyTorch and any innovative solutions you've implemented.
✨Tip Number 4
Showcase your collaborative spirit by sharing examples of how you've worked effectively in teams. Emphasizing your ability to share knowledge and drive innovation will resonate well with the startup's culture.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your machine learning experience, especially any end-to-end projects you've executed. Emphasize your expertise in ML, Deep Learning, and frameworks like PyTorch.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and your ability to drive innovation. Mention specific projects or experiences that align with the job description, particularly in synthetic data generation or LLM training.
Showcase Technical Skills: Clearly outline your technical skills, especially your proficiency in Python and any experience with GPU-based training environments. This will help demonstrate your fit for the role.
Highlight Collaboration Experience: Since the role emphasizes teamwork, include examples of how you've successfully collaborated in previous roles. This could be through cross-functional projects or knowledge-sharing initiatives.
How to prepare for a job interview at Ethiq
✨Showcase Your ML Expertise
Be prepared to discuss your hands-on experience with machine learning projects. Highlight specific examples where you executed end-to-end ML processes, focusing on the challenges you faced and how you overcame them.
✨Demonstrate Technical Proficiency
Familiarize yourself with the latest frameworks like PyTorch and be ready to discuss your experience with deep learning and large language models. If you have advanced Python skills, make sure to mention them as they are a bonus.
✨Discuss Synthetic Data Generation
Since the role involves generating synthetic datasets, prepare to talk about any relevant experience you have in this area. Discuss the techniques you've used and how they contributed to model performance.
✨Emphasize Collaboration Skills
This position values teamwork, so be ready to share examples of how you've successfully collaborated with cross-functional teams. Highlight your ability to share knowledge and innovate together in a fast-paced environment.
