At a Glance
- Tasks: Drive product vision with hands-on coding and collaboration in machine learning projects.
- Company: Join HubSpot's innovative AI Foundations Group and make an impact.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on collaboration and innovation.
- Why this job: Lead cutting-edge AI projects and mentor fellow engineers while shaping the future of technology.
- Qualifications: Expertise in machine learning techniques and a passion for building scalable systems.
The predicted salary is between 70000 - 90000 £ per year.
The Predictive Models team is part of the AI Foundations Group at HubSpot and partners closely with the Predictive AI Platform team to deliver the next generation of predictive insights, scoring and recommendation models.
As a Staff Machine Learning Engineer on the Predictive AI Models team at HubSpot, you’ll take on many responsibilities—leveraging deep expertise in machine learning to drive product vision forward through strong collaboration and hands‑on coding.
Key Qualifications
- Have a long track record of delivering high‑value, high‑impact cross‑team projects; Staff MLEs are senior individual contributors expected to raise the bar for the engineering organization.
- Wish to stay hands‑on in all technical aspects while leading by example through collaboration with cross‑functional and internal stakeholders.
- Have a history of developing solutions that have had an outsized impact on a large organization’s business goals.
- Provide strategic direction for major projects.
- Regularly mentor and teach engineers in their areas of expertise.
- Demonstrate pragmatic decision‑making and problem‑solving abilities.
- Have expert understanding of a range of ML techniques (e.g., deep learning, optimization, regression, transformers, large language models, transfer learning, etc.) and tools (scikit‑learn, PyTorch, TensorFlow, etc.).
- Expert in crafting the right architecture for a variety of ML problems from business requirements, often identifying where ML can be effective in adjacent areas.
- Analyze beyond offline and online metrics, considering privacy, bias, security, and maintainability of models.
- Show enthusiasm for building reliable, scalable systems.
- Guide teams beyond the status quo; lead toward new possibilities while building a shared path forward.
- Deep expertise in predictive AI concepts such as recommendation systems, classification, ranking, and relevancy.
- Embodies our engineering team values.
If you need accommodations or assistance due to a disability, please reach out to us using this form. This information will be treated as confidential and used only for the purpose of determining an appropriate accommodation for the interview process.
Staff Machine Learning Engineer in London employer: HubSpot, Inc.
HubSpot is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the role of Staff Machine Learning Engineer. With a strong emphasis on employee growth, HubSpot offers numerous opportunities for mentorship and hands-on involvement in impactful projects, all while being part of a dynamic team dedicated to pushing the boundaries of predictive AI. Located in a vibrant tech hub, employees benefit from a supportive environment that encourages creativity and professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at HubSpot. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repo showcasing your machine learning projects. This is your chance to demonstrate your hands-on experience and problem-solving abilities.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on your ML techniques and tools. Mock interviews with friends or using online platforms can help you feel more confident.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in being part of the StudySmarter team.
We think you need these skills to ace Staff Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the key qualifications mentioned in the job description. Highlight your experience with machine learning techniques and any impactful projects you've worked on. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about predictive AI and how your skills align with our needs. We love seeing enthusiasm and a clear understanding of the role.
Showcase Your Projects:If you've worked on relevant projects, don't hold back! Include links to your GitHub or any other portfolio that showcases your hands-on coding skills and problem-solving abilities. We appreciate seeing real-world applications of your expertise.
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 makes the process smoother for everyone involved!
How to prepare for a job interview at HubSpot, Inc.
✨Know Your ML Stuff
Make sure you brush up on your machine learning techniques and tools. Be ready to discuss deep learning, regression, and the frameworks like TensorFlow and PyTorch. They’ll likely ask you to explain how you've applied these in past projects, so have some solid examples ready.
✨Showcase Your Impact
Prepare to talk about specific projects where your contributions made a significant difference. Highlight how your work aligned with business goals and led to measurable outcomes. This will demonstrate your ability to deliver high-value projects that resonate with their needs.
✨Collaboration is Key
Since this role involves working closely with cross-functional teams, be ready to share experiences where you successfully collaborated with others. Discuss how you’ve mentored peers or led teams, as they’ll want to see your leadership skills in action.
✨Think Beyond the Code
Be prepared to discuss the broader implications of your work, such as privacy, bias, and security in machine learning models. Show that you understand the importance of maintainability and ethical considerations in AI, which will set you apart as a candidate who thinks critically about their impact.
