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- 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 remote work flexibility.
- 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 deployment experience.
- Other info: Ideal for entrepreneurial engineers looking to make an impact in AI/ML.
The predicted salary is between 96000 - 128000 £ 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 & 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 & efficiency. You’ll 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 & infrastructure.
- Collaborate with cross-functional teams to enhance product features, based on client feedback.
- Work with Python, PyTorch, Tensorflow, Kubernetes, Docker & 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 & 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 specific technologies mentioned in the job description, such as Python, PyTorch, TensorFlow, Kubernetes, and Docker. Having hands-on experience or projects showcasing your skills with these tools will make you stand out during discussions.
✨Tip Number 2
Prepare to discuss real-world examples of how you've solved complex problems in ML deployment. Think about challenges you've faced and how you optimised solutions, as this will demonstrate your problem-solving skills and customer-centric approach.
✨Tip Number 3
Network with professionals in the AI/ML space, especially those who have experience in product engineering roles. Engaging with communities on platforms like LinkedIn can provide insights into the company culture and expectations, which can be beneficial during interviews.
✨Tip Number 4
Showcase your entrepreneurial mindset by discussing any relevant side projects or initiatives you've undertaken. This could include contributions to open-source projects or personal ventures that highlight your ability to innovate and drive results in a fast-paced environment.
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-centric skills.
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 of how you've effectively liaised with customers or cross-functional teams. This will demonstrate your ability to work collaboratively and address client needs.
How to prepare for a job interview at Few&Far
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and any relevant frameworks like PyTorch or TensorFlow. Bring examples of past 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 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 Scenarios
Expect to face technical challenges during the interview. Practice explaining your thought process when solving problems, especially those related to ML deployment and optimisation, as this reflects your problem-solving mindset.
✨Communicate Effectively
Since the role involves liaising with customers, practice clear and concise communication. Be ready to discuss how you’ve successfully collaborated with cross-functional teams in the past, highlighting your customer-centric approach.
