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For Companies At a Glance
- Tasks: Shape innovative ML features to enhance global hardware support.
- Company: Join Mavenoid, a forward-thinking tech company with a collaborative spirit.
- Benefits: Enjoy remote work flexibility, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact in the ML field while working with cutting-edge technologies.
- Qualifications: 4+ years in ML/NLP, experience with Docker and GCP services.
- Other info: Dynamic team environment with excellent career advancement potential.
The predicted salary is between 48000 - 72000 £ per year.
Join Mavenoid as a Senior Machine Learning Engineer and shape the next product features to help people around the world improve support for their hardware devices. You will help process large volumes of textual conversations, search queries, and documents (over 1M text conversations per month) and assess new LLM and NLP models to build and improve ML features in our products.
Technical Stack
- Python, NLP/ML libraries (langchain, langfuse, huggingface, PyTorch, etc.)
- LLM providers (OpenAI, Anthropic, Google, Mistral) and hosted models
- Docker on GCP cloud services
Way of Working
- Small team with shared responsibilities
- Focus on shipping to production and seeing usage
- Keep up with ML developments and balance speed and code quality
You Will
- Work fully remote and meet in person a few times a year
- Own specific features from scoping to production delivery
- Evaluate ideas and propose metrics to explore/implement/ship new things
- Contribute to ML models, features, service architecture, and platform at scale
Qualifications
- ML engineer who cares about product and user outcomes
- At least 4 years of industry experience in ML/data-science, specifically NLP/generative and with conversational data
- Experience with ML problem-solving, diagnosing errors, and hypothesising next steps
- Experience shipping ML services using Docker, GCP services (Cloud Run, Vertex), and CI/CD practices
- Experience with real-time LLM services for RAG conversational systems in production
- Voice or agentic system experience is a plus
- Experience working in a compact ML team with shared ownership
Responsibilities
- Scope, build, and deliver ML features to production
- Think ahead for long-term ML development in the product
- Follow software and ML engineering best practices to keep things humming
Day‑to‑Day At The Individual Level
- 40% exploring/developing ML/NLP problems
- 10% ensuring ML features solve the right problem with the right assumptions with the product team
- 30% shipping for production and keeping live features
- 20% free exploration/investigation for long term
Onboarding Timeline
- First month: complete remote onboarding, meet teams, familiarize with platform, ramp up codebase, focus on one feature to evaluate metrics and propose next steps.
- Three months: work on one feature improvement, collaborate on architecture and product, take over a service and push the envelope, tackle new features from data exploration to feasibility and concept assessment.
- Six months: propose and implement first large platform or architecture change, become familiar with CI/CD/evaluation pipeline, own part of the platform, identify improvement areas.
Seniority Level: Mid‑Senior level
Employment Type: Full‑time
Job Function: Engineering and Information Technology
Industries: Software Development
Senior Machine Learning Engineer in London employer: Mavenoid
Contact Detail:
Mavenoid Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with other ML engineers. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those involving NLP and LLMs. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail, especially how you've tackled real-world ML problems.
✨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 highlight your experience with Docker, GCP, and any relevant ML frameworks.
We think you need these skills to ace Senior Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with ML and NLP, especially any projects that involved conversational data. We want to see how your skills align with the role, so don’t be shy about showcasing relevant achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for the Senior Machine Learning Engineer position. Share your passion for ML and how you can contribute to our mission of improving support for hardware devices.
Showcase Your Technical Skills: Since we’re all about Python and various ML libraries, make sure to mention your proficiency in these areas. If you’ve worked with Docker or GCP services, give us the details – we love seeing hands-on experience!
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 shows you’re keen on joining our team!
How to prepare for a job interview at Mavenoid
✨Know Your Tech Stack
Familiarise yourself with the specific tools and technologies mentioned in the job description, like Python, Docker, and various NLP/ML libraries. Be ready to discuss your experience with these technologies and how you've used them in past projects.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled ML problems, especially those related to NLP and conversational data. Highlight your thought process when diagnosing errors and hypothesising next steps, as this will demonstrate your analytical skills.
✨Understand the Product Impact
Mavenoid is looking for someone who cares about product and user outcomes. Be prepared to discuss how your work in ML can directly improve user experiences and support for hardware devices. Show that you understand the importance of aligning technical solutions with user needs.
✨Emphasise Team Collaboration
Since you'll be working in a small team with shared responsibilities, highlight your experience in collaborative environments. Discuss how you've contributed to team projects and how you handle shared ownership of features, as this will resonate well with their way of working.
