Principal Machine Learning Engineer

Principal Machine Learning Engineer

Full-Time 80000 - 100000 £ / year (est.) Home office (partial)
Anaplan

At a Glance

  • Tasks: Lead the design and deployment of innovative AI and machine learning systems.
  • Company: Join a forward-thinking tech company committed to diversity and inclusion.
  • Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
  • Other info: Dynamic work environment with a focus on collaboration and career advancement.
  • Why this job: Make a real impact by building cutting-edge AI features that transform business planning.
  • Qualifications: Expertise in AI, ML, and software engineering with a strong project delivery record.

The predicted salary is between 80000 - 100000 £ per year.

We're seeking a Principal Machine Learning Engineer who can work across the full stack of Anaplan AI applications, from model integration and prompt engineering to building intuitive user interfaces. You'll build production‑ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills.

Your Impact

  • Lead the architecture, design, and deployment of scalable Generative AI and Machine learning systems into production environments.
  • Develop end‑to‑end GenAI features including backend API services, model integration, model monitoring, evaluations and deployments.
  • Integrate and optimise LLMs for specific use cases in business planning, including prompt engineering, RAG implementation.
  • Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language.
  • Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics.
  • Design and develop APIs that expose AI capabilities to Anaplan's platform and third‑party integrations.
  • Optimise model inference pipelines for performance, cost and scalability in production environments.
  • Implement monitoring, logging, and observability for GenAI systems to track usage, errors and model behaviour.
  • Collaborate with data scientists to productionise ML models and forecasting algorithms.

Your Skills

  • Extensive hands‑on professional experience in the field of Artificial Intelligence, Machine Learning, or related engineering domains.
  • End‑to‑end exposure in model lifecycle development, including extensive experience training and deploying ML models in production environments.
  • Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
  • Experience in fine‑tuning LLMs for domain‑specific enterprise applications.
  • Strong expertise in MLOps and LLMOps, ensuring scalable, reliable and monitorable model deployments.
  • Experience with agentic frameworks and autonomous agent architectures.
  • Proficiency in Python and modern software development practices (testing, code review, CI/CD).
  • Proven track record of delivering complex technical projects on time with high quality.
  • Advanced degree (Master's or Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning or a strongly related quantitative field.
  • Hands‑on experience with cloud‑native ML infrastructure platforms.
  • Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models.
  • Experience with model serving frameworks (vLLM, TensorRT, Ray).
  • Experience with A/B testing and experimentation frameworks for AI features.
  • Contributions to open‑source ML projects or research publications.
  • Experience with model observability tools (LangSmith, W&B, MLflow).

Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)

We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day! We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation. As set forth in Anaplan’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

Principal Machine Learning Engineer employer: Anaplan

Anaplan is an exceptional employer that champions innovation and inclusivity, making it a prime choice for a Principal Machine Learning Engineer. With a strong commitment to diversity, equity, inclusion, and belonging, employees thrive in a collaborative environment that fosters professional growth and encourages authentic self-expression. Located in a vibrant tech hub, Anaplan offers competitive benefits, opportunities for career advancement, and the chance to work on cutting-edge AI technologies that empower business users globally.

Anaplan

Contact Details:

Anaplan Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Principal Machine Learning Engineer

Tip Number 1

Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.

Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and machine learning. This gives potential employers a taste of what you can do.

Tip Number 3

Prepare for interviews by practising common questions and coding challenges. We recommend doing mock interviews with friends or using platforms that simulate real interview scenarios.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!

We think you need these skills to ace Principal Machine Learning Engineer

Machine Learning
Generative AI
Model Integration
Prompt Engineering
Conversational AI
MLOps
LLMOps

Some tips for your application 🫡

Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your hands-on experience with AI and ML, and don’t forget to mention any relevant projects or achievements that showcase your expertise.

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you’re passionate about the role and how your background makes you a perfect fit. Be sure to connect your experiences with the specific requirements mentioned in the job description.

Showcase Your Projects:If you've worked on any interesting AI or ML projects, make sure to include them in your application. Whether it's open-source contributions or personal projects, we love seeing practical examples of your work and how you’ve tackled challenges.

Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing candidates who take the initiative!

How to prepare for a job interview at Anaplan

Know Your Tech Inside Out

Make sure you’re well-versed in the latest trends and technologies in AI and machine learning. Brush up on your knowledge of LLM APIs, prompt engineering, and MLOps. Being able to discuss these topics confidently will show that you’re not just familiar with the basics but are ready to dive deep into the role.

Showcase Your Projects

Prepare to talk about specific projects where you've successfully implemented ML models or built AI features. Highlight your role in the architecture, design, and deployment processes. Use concrete examples to demonstrate your problem-solving skills and how you’ve delivered complex technical projects on time.

Understand the Business Context

Familiarise yourself with how generative AI can impact business planning workflows. Be ready to discuss how your technical skills can translate into real-world applications that empower users. This shows that you’re not just a techie but also understand the broader implications of your work.

Ask Insightful Questions

Prepare thoughtful questions about the company’s approach to AI and machine learning. Inquire about their current projects, challenges they face, or how they measure success in their AI initiatives. This demonstrates your genuine interest in the role and helps you assess if the company is the right fit for you.