Mavenoid
Senior Machine Learning Engineer
Remote
Full Time
#Product
#Engineering
#Python
#NLP
#Huggingface
#PyTorch
#Docker
#GCP
#CI CD
Mavenoid is looking for a Senior Machine Learning Engineer
About us
Mavenoid is the Intelligent Support Platform for products and devices. Our purpose-built technology delivers best-in-class customer support with intelligent troubleshooting and personalized remote support. Our product provides manufacturers and sellers genius-level customer support while reducing costs.
Having raised our Series B, we’re in 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. We were founded in Stockholm, Sweden, but now operate globally as a remote-first company, with team members located across Sweden, the United Kingdom, the United States, and more.
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 consists mostly of textual conversations, search queries and documents (more than 1M text conversations per month and growing volume on voice). You will help to process this data and assess new LLM and NLP models to build and improve the set of ML features in the products.
Tech stack:
- Python
- NLP/ML libs, including langchain, langfuse, huggingface, pytorch (among others)
- Major LLM providers (OpenAI, Anthropic, Google, Mistral) and hosted models
- Deploying with docker on GCP cloud services
We are pragmatic on which tool to use for each approach, as long as it can be properly packaged for production.
Way of working
We are a small team — by design — and share responsibilities. We care about:
- Shipping to production and see usage
- Keeping up with the ML developments
- Balance between speed and codebase quality
You will:
- Work fully remote and meet IRL few times a year
- Focus on specific features and own the process from scoping to production delivery
- Evaluate ideas and propose the right metrics to explore/implement/ship new things
- Contribute on ML models and features but also service architecture and the platform at scale
Qualifications
Responsibilities
Day-to-day at the individual level:
- 40% exploring/developing ML/NLP problem
- 10% making sure the ML features are solving the right problem with the right assumptions with product team
- 30% shipping for production and keeping live features
- 20% free exploration/investigation for long term
In your first month, you will
- Complete Mavenoid’s remote onboarding program
- Meet with the ML/Product/CS teams to understand what is being worked on
- Familiarize yourself with our platform and product, and processes
- Ramp up the codebase with co-working sessions and/or time on your side
- Focus on one feature to understand the evaluation metrics and propose a step ahead in accuracy/efficiency/performance
In your 3 months, you will
- Work on one first feature improvement to go over 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 one or more new feature, from data exploration to feasibility and concept assessment, in collaboration with the product lead.
In your 6 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.
Our Core Values
Win as a Team - Teams are not just extensions of leaders, but are instead a composite of individuals, each with their own strengths. We need to work together in order to scale. And, it’s more fun this way!
Teach & Be Taught - As a company, we believe that there is always a way to improve how you work, and therefore it is important to be consistently open to learning. Also, in a fast-growing company, roles & contexts shift, and it is important to be able to adjust. Teaching others is the flip side of that – it's a great way to build deeper understanding of the topics you teach, and also an important tool to scale the organization as you step into new roles and responsibilities.
Cut out the B.S. - Get to the bottom of the issue and surface the information needed to make good decisions.
Pick up the Pace - As a startup, our structural advantage is speed, but only if we act with urgency. Don’t leave for tomorrow what you can do today.
Eyes on the Ball - Don’t get distracted from what is most important, right now. In a startup, there are a million different things that you can do in any situation, and it’s necessary to have a consistent focus over time on the things that have the highest impact.
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