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For Companies At a Glance
- Tasks: Collaborate with customers to optimise ML deployment solutions using Python.
- Company: Join a fast-growing US scale-up focused on empowering engineering teams.
- Benefits: Enjoy a competitive salary, stock options, and fully remote work.
- Why this job: Be part of a dynamic team from top tech companies, tackling real-world AI challenges.
- Qualifications: 5+ years in Backend Software Engineering, ideally with ML experience and a Computer Science degree.
- Other info: This role offers insights into AI/ML implementation at scale, perfect for entrepreneurial engineers.
The predicted salary is between 96000 - 144000 £ per year.
Forward Deployed Product Engineer (Python) - Fully Remote within the UK - Up to £160k + Stock + Benefits
Join a US scale-up on a mission to empower Engineering teams to deliver their best work, through simplifying the deployment of Machine Learning models. As they expand their global footprint, raised Series C funding and have grown over 30% in 3 months, they’re seeking a talented Forward Deployed Engineer to join the UK team!
About the Role
As a Forward Deployed Engineer you will collaborate directly with customers to understand challenges, engineering ML-based deployment solutions. You will be instrumental in ensuring clients achieve optimal outcomes with their models, focusing on aspects like optimisation, scalability and efficiency. You will work alongside teams that have joined from world-class tech businesses like NVIDIA, Amazon, Datadog, Vercel, Meta, GitHub and Uber.
Key Responsibilities
- Partner with customers to identify and address their ML deployment needs
- Implement and optimise ML solutions using Python, open-source tools and infrastructure
- Collaborate with cross-functional teams to enhance product features, based on client feedback
- Work with Python, PyTorch, Tensorflow, Kubernetes, Docker and cloud platforms
Ideal Candidates have
- 5+ years of Backend (Python) Software Engineering experience in a fast-paced, high-growth, product environment, ideally as a Co-Founder or Founding Engineer
- Some interest or experience with the lifecycle of ML model development and deployment
- Computer Science degree or similar field of study
- Excellent English communication skills: proven experience liaising effectively with customers (other Software Engineers or ML Engineers)
- Strong problem-solving skills and a proven customer-centric, Product Engineering mindset.
This role provides a view into the opportunities and challenges companies face implementing AI/ML solutions at scale and is ideal for Entrepreneurial Engineers. Apply with an updated CV to learn more!
Forward Deployed Engineer - Remote UK employer: Few&Far
Contact Detail:
Few&Far Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Forward Deployed Engineer - Remote UK
✨Tip Number 1
Familiarise yourself with the latest trends in Machine Learning and deployment technologies. Being well-versed in tools like PyTorch, TensorFlow, Kubernetes, and Docker will not only boost your confidence but also demonstrate your commitment to staying current in this fast-evolving field.
✨Tip Number 2
Network with professionals in the industry, especially those who have experience in ML deployments. Engaging with communities on platforms like LinkedIn or attending relevant meetups can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Prepare to discuss real-world examples of how you've tackled challenges in ML deployment. Be ready to share specific instances where you optimised solutions or improved scalability, as this will showcase your problem-solving skills and customer-centric approach.
✨Tip Number 4
Research the company’s recent projects and their impact on engineering teams. Understanding their mission and how they empower clients will help you tailor your conversations during interviews, making you a more appealing candidate.
We think you need these skills to ace Forward Deployed Engineer - Remote UK
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in Backend Software Engineering, particularly with Python. Emphasise any work you've done with ML model development and deployment, as well as your problem-solving skills.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for engineering and your understanding of ML deployment challenges. Mention specific experiences where you've collaborated with customers to solve problems, as this role requires strong customer interaction.
Showcase Technical Skills: In your application, clearly list your technical skills, especially those mentioned in the job description like Python, PyTorch, TensorFlow, Kubernetes, and Docker. Provide examples of how you've used these technologies in past projects.
Highlight Communication Skills: Since excellent communication is key for this role, include examples in your application that demonstrate your ability to liaise effectively with clients and cross-functional teams. This could be through previous roles or specific projects.
How to prepare for a job interview at Few&Far
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and the specific tools mentioned in the job description, such as PyTorch, TensorFlow, Kubernetes, and Docker. Highlight any projects where you've implemented ML solutions, as this will demonstrate your hands-on expertise.
✨Understand the Company’s Mission
Research the company’s goals and how they aim to empower engineering teams. Being able to articulate how your skills align with their mission will show your genuine interest in the role and the company.
✨Prepare for Problem-Solving Questions
Expect to face technical challenges or case studies during the interview. Practice explaining your thought process clearly and concisely, as this will showcase your problem-solving abilities and customer-centric mindset.
✨Communicate Effectively
Since excellent communication skills are crucial for this role, practice articulating your thoughts and experiences. Be ready to discuss how you’ve successfully liaised with customers in the past, as this will highlight your ability to work collaboratively.
