At a Glance
- Tasks: Join a passionate team to build and integrate ML models for innovative tools.
- Company: A creative tech company that values diversity and collaboration.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Dynamic environment with excellent career advancement opportunities.
- Why this job: Make a real impact by working on cutting-edge machine learning projects.
- Qualifications: Strong programming skills and experience with MLOps/LLMOps frameworks.
The predicted salary is between 60000 - 80000 £ per year.
The company is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives.
As an Applied Machine Learning Engineer in the Developer Publications Intelligence team, you will join a multi-discipline team of passionate Machine Learning and Software engineers to build and integrate ML models into existing and future tools produced by the company for third-party developers. We strive for excellence and believe strongly in the quality of our output. As a member of the team, you will work alongside a team of domain experts in specific core subject areas, enable cross functional collaboration with other departments at the company, contribute to architecture discussions, code review and proposals.
Responsibilities
- Driving MLOps/LLMOps excellence within the team: including evaluation pipelines, monitoring, observability, and deployment best practices
- Building and maintaining LLM evaluation pipelines to assess model quality, track regressions, and support continuous improvement cycles
- Engaging in code review, pair programming and architecture discussions with other members of the team
Preferred Qualifications
- BS, MS or PhD in Computer Science, Artificial Intelligence, or Machine Learning (or equivalent experience)
- Experience with: Xcode, Swift and developing for the company’s platforms
- Familiarity with on-device LLMs
Minimum Qualifications
- Strong programming skills (Python, Swift, Go or other language)
- Experience with MLOps/LLMOps toolkits and frameworks
- Comprehensive knowledge and hands‑on experience with LLM evaluations
- A learning attitude to continuously improve self and team
Applied Machine Learning Engineer - Developer Publications employer: United States Digital Space LLC
At our company, we foster a vibrant work culture where creativity and collaboration thrive, making it an exceptional place for an Applied Machine Learning Engineer. With a strong commitment to employee growth, we offer opportunities for continuous learning and innovation, allowing you to contribute to impactful projects that change lives. Located in a dynamic environment, our diverse team encourages unique perspectives, ensuring that every voice is heard and valued.
Contact Details:
United States Digital Space LLC Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Applied Machine Learning Engineer - Developer Publications
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at United States Digital Space LLC or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
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✨Tap into Online Developer Communities
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We think you need these skills to ace Applied Machine Learning Engineer - Developer Publications
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at United States Digital Space LLC.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at United States Digital Space LLC and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at United States Digital Space LLC
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If United States Digital Space LLC uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
