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Senior Machine Learning Engineer

About us

Mavenoid is the world’s first hardware support platform. We’ve built a virtual assistant and other tools that help customers set up, use, and troubleshoot everything from dishwashers and printers to robotic lawnmowers and electric scooters. With iconic brands like HP and Jabra as clients and $40 million in funding from top VC firms like Creandum and Point Nine Capital, we’re reinventing technical support for physical products. Having recently raised our Series B, we’re entering an exciting phase of growth but are still small enough for each new person to have a big impact on the company as a whole. As an international virtual-first company, we have office optional culture with Mavens located all over North America and Europe.

The role

You will be part of the ML team at Mavenoid, shaping the next product features to help people around the world get better support for their hardware devices. The core of your work will be to understand users’ questions and problems to fill the semantic gap. The incoming data consist of textual conversations, search queries (in the order of 100Ks conversations or 1Ms of search queries per month), and documents. You will help to process this data and assess new NLP models to build and improve the set of ML features in the products. Pragmatic and focused on efficiency, you will work from exploration to delivery in cloud services.

Our stack is in python and relies on GCP cloud services. On the library side, you will use the well-known NLP/deep learning packages, including spacy, huggingface, and openAI GPT3 API (among others). But we are not dogmatic but pragmatic on which library to use for each approach as long as it can be packaged for production.
In your first month, you will
  • Complete Mavenoid’s remote onboarding program.
  • Meet with the ML/Product teams to understand what is being worked on.
  • Familiarize yourself with our platform and product, and processes.
  • Ramp up the codebase with a co-working session and/or time on your side.
  • Focus on a feature to understand the evaluation metrics and propose a step ahead in accuracy/efficiency/performance.
In your first three months, you will
  • Work on one first feature improvement to go over the explore/implement/evaluate/ship loop
  • Collaborate with the rest of the team to bring your input on the system architecture and the product.
  • Take over one service and push the envelope.
  • Tackle a new feature from data exploration to feasibility and concept assessment in collaboration with the product lead.
In your first six months, you will
  • Propose, discuss, coordinate and implement your first large platform or architecture change.
  • Be familiar with a large portion of the platform, including the details of our CI/CD/evaluation pipeline, machine learning services, and integrations to external systems.
  • Own a part of the platform and be able to identify areas of improvement.
Responsibilities
  • Collaborate with stakeholders and other engineers to conceptualize, build and test new ML features.
  • Apply the right tools for the job and solve business problems with real-world challenges.
  • Support the ML team to ensure high spirits and productivity.
  • Develop reliable and effective machine-learning operations and processes.
  • Ensure ML services and models are reliable and performant
  • Ensure and track ML reliability
Qualifications
  • At least four years of industry experience in AI/ML/data-science roles, specifically for NLP and conversational data.
  • You love working on hard and valuable problems, no matter how challenging.
  • You can solve a wide breadth of problems in more direct or robust ways than most.
  • Fluency in Python and the machine-learning ecosystem.
  • Experience in small ML teams where responsibilities and ownership are shared.
  • Experience deploying ML models as cloud services and working with MLOps to scale.
What we offer

- Remote-first policy: Work from home or, if you prefer, from one of our offices in Stockholm, Sweden, New York City, US, or Amsterdam, The Netherlands.
- Employees’ work-life balance: flexible working hours and 25 days paid leave + national bank holidays.
- Employees’ wellness: free food during working hours, bi-weekly meditation sessions, and up to $500 as a Health Perk.
- Remote/home setup: latest generation Mac, large screens, ergonomic desks/chairs, and other equipment you might need.
- A career opportunity where your professional growth is in focus: unlimited books, three days off per year to focus on personal development, and up to $2,400 for courses, conferences, and other learning material.
- Regular company trips and remote activities.


For those working in the US or Canada:
- Unlimited sick leave
- Paid health insurance (medical, dental, and vision)
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