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- Tasks: Deploy and enhance machine learning models in real-world energy and industrial settings.
- Company: Exciting deep tech AI startup backed by top-tier investors.
- Benefits: Remote work, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact on global energy efficiency with cutting-edge technology.
- Qualifications: Proficient in Python, deep learning frameworks, and experience in productionising ML models.
- Other info: Join a dynamic team at the forefront of AI and physical science.
The predicted salary is between 36000 - 60000 £ per year.
You will deploy and harden machine learning components in real-world energy and industrial environments. This role bridges the gap between research and production by operationalising physics-informed and deep learning models under real-world constraints. You will ensure the robustness, stability, and explainability of AI systems within complex physical infrastructure and field environments.
Location: Remote
Why this role is remarkable:
- Deploy cutting-edge physics-informed ML models that have a direct impact on global energy and industrial efficiency.
- Work at a well-funded startup backed by top-tier VCs, operating at the intersection of deep learning and physical science.
- Lead the transition from lab-based research to production-grade deployments in complex, high-stakes operational environments.
What you will do:
- Own and deploy end-to-end ML pipelines including data validation, feature extraction, model serving, and performance monitoring.
- Adapt foundation models and algorithms to site-specific industrial data and infrastructure constraints.
- Collaborate with research teams to translate novel physics-informed methods into production-grade, reliable systems.
The ideal candidate:
- Proficient in Python and deep learning frameworks like PyTorch or JAX, with experience in Docker and Kubernetes.
- Strong background in applied ML for time series or operational AI within industrial or energy contexts.
- Proven experience productionising ML models with a focus on CI/CD integration, observability, and system reliability.
Machine Learning Engineer at deep tech industrial AI startup employer: Jack & Jill
Contact Detail:
Jack & Jill Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer at deep tech industrial AI startup
✨Tip Number 1
Get to know the company inside out! Research their projects, values, and culture. This will help you tailor your conversations and show that you're genuinely interested in being part of their team.
✨Tip Number 2
Network like a pro! Connect with current employees on LinkedIn or attend industry events. A friendly chat can sometimes lead to insider info or even a referral, which can give you a leg up in the hiring process.
✨Tip Number 3
Practice makes perfect! Prepare for technical interviews by working on relevant projects or coding challenges. This will not only boost your confidence but also demonstrate your skills in real-world scenarios.
✨Tip Number 4
Don’t forget to apply through our website! Chat with Jack to get personalised advice and ensure Jill considers you for this role. It’s a free service that could really help you land that dream job!
We think you need these skills to ace Machine Learning Engineer at deep tech industrial AI startup
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Machine Learning Engineer role. Highlight your experience with Python, deep learning frameworks, and any relevant projects that showcase your skills in deploying ML models in industrial settings.
Showcase Your Impact: When detailing your past experiences, focus on the impact you've made. Use metrics and examples to illustrate how your work has improved efficiency or stability in previous roles, especially in energy or industrial contexts.
Be Clear and Concise: Keep your application clear and to the point. Avoid jargon unless it's necessary, and make sure your passion for AI and machine learning shines through. We want to see your personality as well as your qualifications!
Apply Through Our Website: Don’t forget to apply through our website! Click 'Talk to Jack' so we can get to know you better. This way, we can ensure your application gets the attention it deserves and help you land that dream job.
How to prepare for a job interview at Jack & Jill
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python and the deep learning frameworks mentioned, like PyTorch or JAX. Brush up on your knowledge of Docker and Kubernetes too, as these are crucial for deploying ML models in real-world environments.
✨Showcase Real-World Applications
Prepare to discuss how you've applied machine learning in industrial or energy contexts. Be ready to share specific examples of how you've operationalised models and ensured their robustness and reliability in high-stakes situations.
✨Understand the Company’s Mission
Research the startup's focus on global energy efficiency and how they integrate physics-informed models. This will help you align your answers with their goals and demonstrate your genuine interest in their work.
✨Ask Insightful Questions
Prepare thoughtful questions about their current projects and challenges they face in deploying ML models. This shows your enthusiasm and helps you gauge if the company is the right fit for you.
