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, shaping the future of predictive insights.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on collaboration and innovation.
- Why this job: Make a real impact on business goals while mentoring and leading engineering teams.
- Qualifications: Expertise in machine learning techniques and a proven track record in impactful projects.
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 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 vibrant team dedicated to pushing the boundaries of predictive AI. Located in a dynamic environment, employees benefit from a supportive atmosphere that encourages creativity and strategic thinking, making it a truly rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at HubSpot. A friendly chat can open doors that a CV 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 expertise and creativity.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on your ML concepts and coding skills. Mock interviews with friends or online platforms can really help.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Staff Machine Learning Engineer
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 cross-team projects you've led. We want to see how you can bring value to our Predictive Models 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 past experiences align with our goals. We love seeing enthusiasm and a clear vision for how you can contribute to our team.
Showcase Your Technical Skills:Don’t hold back on showcasing your technical expertise! Mention specific tools and techniques you’ve used, like PyTorch or TensorFlow, and provide examples of how you've applied them in real-world scenarios. We’re keen to see your 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 serious about joining our team at HubSpot!
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 want to hear about your hands-on experience, so prepare some examples of projects where you’ve applied these skills.
✨Showcase Your Impact
Be prepared to talk about high-value projects you've delivered in the past. Highlight how your contributions have driven business goals and made a significant impact. Use specific metrics or outcomes to illustrate your success and demonstrate your ability to lead cross-team initiatives.
✨Collaboration is Key
Since this role involves working closely with various teams, emphasise your collaboration skills. Share examples of how you’ve worked with different stakeholders to achieve project goals. Show that you can lead by example while also being a team player.
✨Think Beyond the Code
Prepare to discuss not just the technical aspects but also the ethical considerations of machine learning. Talk about how you’ve addressed issues like privacy, bias, and security in your previous work. This will show that you’re not only a tech whiz but also a responsible engineer.
