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- Tasks: Lead the development of cutting-edge AI systems and scalable ML software.
- Company: Innovative tech firm focused on ethical AI solutions.
- Benefits: Unlimited leave, private healthcare, flexible working, and coaching support.
- Other info: Fast-paced environment with opportunities for growth and autonomy.
- Why this job: Make a real impact in AI while mentoring future engineers.
- Qualifications: Expertise in ML frameworks, Python, and cloud platforms required.
The predicted salary is between 70000 - 90000 ÂŁ per year.
About the role
As a Senior Machine Learning Engineer, you will lead the development and deployment of cutting‑edge AI systems for diverse clients. You will design, build, and launch scalable, production‑grade machine‑learning software and infrastructure that meet rigorous operational and ethical standards. This role combines technical expertise, engineering leadership, and client‑facing communication.
What you'll be doing
- Leading technical scoping and architectural decisions for high‑impact ML systems
- Designing and building production‑grade ML software, tools, and scalable infrastructure
- Defining and implementing best practices and standards for deploying machine learning at scale across the business
- Collaborating with engineers, data scientists, product managers, and commercial teams to solve critical client challenges and seize opportunities
- Acting as a trusted technical advisor to customers and partners, translating complex concepts into actionable strategies
- Mentoring and developing junior engineers, actively shaping the team’s engineering culture and technical depth
Who we're looking for
- You understand the full ML lifecycle and have significant experience operationalising models built with frameworks like TensorFlow or PyTorch
- You bring deep expertise in software engineering and strong Python skills, focusing on building robust, reusable systems
- You have demonstrable hands‑on experience with cloud platforms (e.g., AWS, Azure, GCP), including architecture, security, and infrastructure
- You've extensive experience working with container and orchestration tools such as Docker and Kubernetes to build and manage applications at scale
- You thrive in fast‑paced, high‑growth environments, demonstrating ownership and autonomy in driving projects to completion
- You communicate exceptionally well, confidently guiding both technical teams and senior, non‑technical stakeholders
Benefits
- Unlimited annual leave policy
- Private healthcare and dental
- Enhanced parental leave
- Family‑friendly flexibility & flexible working
- Sanctus Coaching
- Hybrid working
Senior Machine Learning Engineer employer: AI Chopping Block, Inc.
Contact Detail:
AI Chopping Block, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the machine learning field and let them know you're on the lookout for opportunities. Attend meetups or webinars related to AI and ML; you never know who might be hiring or can refer you to someone.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving TensorFlow or PyTorch. Share your work on platforms like GitHub and make sure to highlight any production-grade systems you've built.
✨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 need to communicate effectively with both technical teams and non-technical stakeholders.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to reflect how your experience aligns with the role of Senior Machine Learning Engineer and the impact you can make.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Machine Learning Engineer role. Highlight your experience with ML frameworks like TensorFlow or PyTorch, and don’t forget to showcase your cloud platform expertise. We want to see how your skills align with what we’re looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning and how your past experiences make you a great fit for our team. Remember, we love seeing your personality come through, so don’t hold back!
Showcase Your Projects: If you’ve worked on any impressive ML projects, make sure to mention them in your application. Whether it’s a personal project or something from a previous job, we want to see your hands-on experience and how you’ve tackled real-world challenges.
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 gives you a chance to explore more about StudySmarter and what we stand for!
How to prepare for a job interview at AI Chopping Block, Inc.
✨Know Your ML Lifecycle
Make sure you can confidently discuss the full machine learning lifecycle. Be prepared to explain how you've operationalised models using frameworks like TensorFlow or PyTorch, and share specific examples of your past projects.
✨Showcase Your Technical Skills
Brush up on your Python skills and be ready to demonstrate your software engineering expertise. You might be asked to solve a coding problem or discuss your experience with cloud platforms like AWS, Azure, or GCP, so have relevant examples at the ready.
✨Communicate Clearly
Since this role involves client-facing communication, practice explaining complex technical concepts in simple terms. Think about how you would translate your work to non-technical stakeholders and be ready to showcase your mentoring experience with junior engineers.
✨Prepare for Collaboration Questions
Expect questions about teamwork and collaboration. Reflect on your experiences working with cross-functional teams, and be ready to discuss how you've solved client challenges and seized opportunities in fast-paced environments.