At a Glance
- Tasks: Join our AI team to develop cutting-edge machine learning features and enhance product management tools.
- Company: Productboard is a leading product management platform, empowering teams to build impactful products since 2014.
- Benefits: Enjoy a dynamic startup culture, remote work options, and opportunities for personal impact in a Unicorn company.
- Why this job: Be part of a mission-driven team that values creativity, collaboration, and continuous improvement in tech.
- Qualifications: Expertise in Python, ML systems, and event-driven architecture; data science background is a plus.
- Other info: Work with top-tier investors and be recognized as part of one of the hottest tech startups.
The predicted salary is between 48000 - 84000 £ per year.
Location: London
When we started in 2014, our focus was on product managers in smaller teams who lacked a great product management tool. Today, we are the leading product management platform, helping enterprise companies with thousands of employees to build products that matter. We believe Productboard's greatest differentiator is enabling our customers to collect, understand, and act upon data from the market, empowering them to organize insights, understand their customers, and align their company around the most impactful opportunities.
We are in search of an experienced Machine Learning Engineer to become a member of our cross-functional team. Your role will span across the entire AI feature development lifecycle.
About the AI team:
- The AI team is a cross-functional product team, composed of backend, frontend, machine learning engineers with PMs and designers.
- We aim to build more copilot features into Insights and other domains, enabling bulk-processing, pre-processing, smart suggestions, and other functionality.
Where are we heading?
To create even more value for customers, we are on a mission to help product teams transform their product management practices, leveraging the power of AI to make impactful product decisions faster through a deeper understanding of different types of data within the Productboard platform (customer feedback, competitors, market intelligence, business strategy, etc.). We also aim to make product teams more effective on tactical and strategic tasks throughout the entire product management lifecycle with AI-powered workflows that augment existing core workflows within Productboard.
Our core challenges:
- Introducing new capabilities into our solutions – a feature store, eliminating the need for manual processing of incoming Insights data, live predictions, co-usage of different vendor LLMs, etc.
- Ensuring data flows from the frontend via GraphQL – asynchronous processing through Kafka in different services, and back to frontend – producing a seamless UX experience.
- Ensuring our core services, which store data from different sources, are ready to scale and meet performance requirements.
- Building a robust agentic infrastructure capable of supporting diverse AI-driven use cases, enabling scalable, autonomous decision-making workflows, and ensuring resilience across various customer scenarios.
We’re looking for experienced engineering minds, who are able to lead big technical projects and act as knowledge multipliers inside and outside of the team. Those who strive to build top-end services and can turn a good system design on paper into a well-tuned working solution.
Our tech stack:
- We write our ML code in Python.
- For scheduling ML pipelines, we rely on orchestration frameworks like Celery and Kubernetes.
- Our real-time services run on AWS and Kubernetes, backed by Git, CI/CD, Docker, Helm, and Kafka.
- For monitoring our services, we use Datadog and Sentry, and for a business overview, we've got Looker in our toolkit.
- Our tech toolbox also includes GraphQL and Postgres, among other technologies.
- LangGraph for agent orchestration and workflow management, combined with LangSmith for observability, monitoring, and evaluation of AI agents.
About you:
We are currently seeking an individual who possesses the following skills and qualities:
- Professional expertise in building Python applications.
- Proficiency in designing, executing, and maintaining ML systems and solutions in a production environment.
- Familiarity with the management of performance and testing of ML systems.
- Practical experience with message queue systems and a grasp of event-driven architecture.
- A background in data science and LLMs would be highly advantageous.
You will help us with:
- Building AI-powered product features.
- Enhancing and sustaining our internal tech stack while identifying and incorporating new state-of-the-art technologies.
- Discovering and experimenting across different domains, creating MVPs and POCs, engaging in discussions about findings with fellow engineers and the product team, and planning the execution.
- Collaborating with other engineers, introducing fresh concepts and methodologies to the team.
The team has recently worked on:
- Delivering LLM solutions to our customers.
- Establishing a Feature store dedicated to storing embeddings for our services.
- Training NLP models, utilized by numerous customers, with daily retraining cycles.
About Productboard:
Productboard is the customer-centric product management platform that helps organizations get the right products to market, faster. Over 5,500 companies, including Zoom, One Medical, Cartier, Microsoft, and Korn Ferry, use Productboard to understand what customers need, prioritize what to build next, and rally everyone around their roadmap.
With offices in San Francisco, Brno, and Prague, Productboard is backed by leading investors. In January 2022, we closed our $125M Series D round, which put us into the Unicorn category of companies, with a valuation of $1.7B. Join at the golden startup age — established stability of a Unicorn with space for individual impact. You’ll enjoy an exciting team atmosphere, building a whole new category of software.
We iterate quickly, and decisions are fast. You’ll have a voice in what we do and see the impact of your work. We are backed by top Silicon Valley investors, giving us access to capital, networks, mentors, and new markets. We are recognized as one of the hottest tech startups on the market today.
About our culture:
Imagine working in a place where everything matters — most importantly, you. At Productboard, values aren’t just something we like to talk about; they’re something we live and breathe. We believe in creating a work environment where:
- People feel empowered, supported, and included.
- Trust and transparency are built into the way we work.
- Creativity, curiosity, and continuous improvement are encouraged and nurtured every day.
We are committed to an inclusive hiring process and provide all candidates with equal opportunity to demonstrate their abilities. Togetherness is one of our core values, and our Diversity Council helps to ensure that we uphold the values of authenticity, humanity, and diversity to create an environment where every person matters.
Senior ML Engineer in AI Team employer: Productboard
Contact Detail:
Productboard Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer in AI Team
✨Tip Number 1
Familiarise yourself with our tech stack, especially Python, AWS, and Kubernetes. Being able to discuss your experience with these technologies in detail will show that you're ready to hit the ground running.
✨Tip Number 2
Engage with our AI features and understand how they integrate into product management. This knowledge will help you demonstrate your enthusiasm for our mission and how you can contribute to enhancing these capabilities.
✨Tip Number 3
Network with current employees or join relevant online communities. This can provide insights into our company culture and the specific challenges our AI team is facing, which you can address during discussions.
✨Tip Number 4
Prepare to discuss your past projects involving machine learning systems and event-driven architecture. Highlighting your practical experience will help you stand out as a candidate who can lead technical projects effectively.
We think you need these skills to ace Senior ML Engineer in AI Team
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning and Python development. Focus on projects that demonstrate your ability to design, execute, and maintain ML systems, as well as any experience with event-driven architecture.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and product management. Mention specific projects or technologies you've worked with that align with the job description, such as AWS, Kubernetes, or message queue systems.
Showcase Your Technical Skills: Include a section in your application that lists your technical skills, particularly those mentioned in the job description. Highlight your proficiency in Python, ML frameworks, and any experience with tools like Celery, Kafka, or Datadog.
Demonstrate Cultural Fit: Research Productboard's culture and values. In your application, mention how your personal values align with theirs, especially regarding creativity, curiosity, and teamwork. This will show that you are not just a fit for the role, but also for the company.
How to prepare for a job interview at Productboard
✨Showcase Your Python Expertise
As a Senior ML Engineer, your proficiency in Python is crucial. Be prepared to discuss specific projects where you've built applications or systems using Python, and highlight any frameworks or libraries you've used that are relevant to the role.
✨Demonstrate Your ML System Knowledge
The interviewers will be keen to understand your experience with designing, executing, and maintaining ML systems in production. Prepare examples of challenges you've faced in this area and how you overcame them, particularly focusing on performance management and testing.
✨Familiarise Yourself with Their Tech Stack
Study the technologies mentioned in the job description, such as AWS, Kubernetes, and Kafka. Being able to discuss how you've used similar tools in past roles will show that you're ready to hit the ground running.
✨Prepare for Collaborative Discussions
Since the AI team is cross-functional, be ready to talk about your experience working with diverse teams, including product managers and designers. Highlight instances where you've introduced new concepts or methodologies that improved collaboration and outcomes.