Golang NLP Jobs in Germany

Job Description

Opinary has one mission: We help people make up their minds. Globally, millions of people use our polling technology to share their opinion, engage in open dialogue, and understand complex debates - all with one simple click. And, by harnessing the latest advances in Machine Learning, NLP, and distributed systems design, our platform ensures that readers get the right question at the right time.

With over 80 million monthly users, we’re one of the fastest-growing startups in the media space. You’ve probably used our tools yourself on publishers like The Times, Spiegel Online, NBC, Huffington Post, or the Independent.

As a Platform Engineer, your technical chops will directly impact today’s debates in the most relevant media outlets.

Who we’re looking for

Sure, we need someone talented. But, most importantly, we are looking for someone who:

• Owns challenges. Who doesn’t back down or say “that’s not my job.”
• Is a great communicator and listener. Likes to collaborate across teams and understand why their project matters to everyone in the company.
• Embodies our values of care and respect. That means caring for and respecting your colleagues as well as your own mental and physical health.
• Is comfortable with designing and developing large distributed systems.
• Has a solid understanding of effective engineering practices (TDD, XP, etc.).
• Has worked in modern cloud platforms such as AWS/GCP.
• Is familiar with the concepts of event-driven architectures.

Your challenges

• You develop software in a compliant and rigorous way, whilst maximizing the value add to our stakeholders: users, brands & publishers.
• You take ownership of the existing codebase and proactively work on improving the stability of it.
• You maintain and monitor the live system, and you are responsible for the swift recovery in case of issues.
• You design and implement new services that support the needs of the stakeholders.
• You enhance our technology stack and lead the implementation of platforms both as well as the systems infrastructure of our product
• You collaborate with our Product Lead to refine the product-market fit
• You work in a close and trustful relationship with the founders, product and sales teams in a cross-discipline agile environment

Your profile

• You had the chance to work in a team on a live project for at least three years as a Software Engineer.
• You approach the problems holistically, and you can make tradeoffs based on data.
• You value coding as your craft and understand that writing software is about solving technical problems - but equally important, something to be maintained and understood by your peers.
• You enjoy pair-programming with your colleagues.
• You had the opportunity to debug a live service, on live traffic, with live users.
• You’re proactive and curious: always eager to learn new things and happy to share your knowledge with others.

What we offer

• We have a diverse and open culture from different professional and personal backgrounds. Our agile team provides the space to directly influence and impact our product positively
• Growth and continuous learning: everyone at Opinary is encouraged to trust in experiments and personally grow - with a generous learning budget to help out
• We provide a flexible working environment. Choose your working hours, take unlimited work-from-home and holidays, and choose your preferred laptop

Job Description

Back is a young software company from Berlin with the mission to enable companies to focus on what they do best. We’re building a collaboration and automation platform to untangle repetitive questions and workflows around the workplace.

You will join our experienced engineering team to build our machine learning pipeline and develop some of our first machine learning supported features. If you are excited about building highly scalable solutions built on a modern stack using best practices then this role is perfect for you.

This position is based in our growing HQ in Berlin.

🔨 What you will do

• You will take ownership of automation features from the beginning - understanding the problem - to the end - deploying the model on production -.
• You will setup the environment to speed up our machine learning development.
• You will implement and tune state-of-the-art ML models to get the best results given the available data.
• You will effectively communicate and document your approach, progress, results and challenges with the team.
• You will help us grow the machine learning team: enforce best practices, interview candidate, etc.

👩‍🔬 Who are we looking for

• You can quickly grasp the business context of the problem and using your knowledge of how the model is going to be used, you can choose the right evaluation metric.
• You can dig deep into the data to choose the right dataset split and identify pitfalls arising from non-iid samples.
• You can combining both your practical and theoretical ML knowledge to set the right priorities when choosing which idea or approach to try next.
• You find the simplest solution to solve complex problems programmatically.
• You find joy in delivering features to your customer rather than doing academic research.
• You like to work in a team and challenge your choices with your peers.

🦾 What challenges will you face

• You'll work on complex NLP problems touching multiple domains: multiple language understanding and feature extraction.
• You'll work on unbalanced datasets, not all our customers are the same size.
• Our customers have different processes, different vocabulary. You will face dual-domain adaptation problems.
• The good news: our application generates labeled data and we capture all the signals of our users' interactions, so you'll focus on training models, not labelling data. Yeah!

🏅Our engineering values

Radical honesty

• We discuss problems and mistakes in the open, with the team, to share our knowledge, opinion, and find the best solutions to make sure they do not happen again.
• We discuss behavioral or personal problems in private, only with the people being involved.
• Our discussions focus on the problem, not on people. People are rarely the problem and we always assume good faith.

Radical transparency

• We do not hide anything inside and outside the team. We voluntarily and constantly share our successes, our mistakes, and our progress.

Radical open-mindedness

• We share our knowledge and experience to find the best solutions as a team, never to be right or the smartest in the room.
• We share our opinion only when we have the willingness to change it.

Radical pragmatism

• We design strategic solutions with a growth mindset. We seek for solutions driving progress at the fastest pace and lowest cost to create progressive long-lasting impact.
• We refuse dogma. We make the best decision for ourselves, in our context.

Customer-first

• We consider success as having a high customer impact and satisfaction.
• Each decision we make must have sooner or later a positive impact on our customers.
• We privilege customer satisfaction over our comfort.
• We refuse to compromise the quality of our product and customer experience.

Camaraderie

• There is no place for competition or ego.
• We thrive at helping each other and sharing knowledge to contribute to everyone’s growth.

🚀 Why Back?

• You’ll join a company that believes in a strong engineering culture. We use modern technologies, best practices, within a team of smart people who want to change the way people work.
• You’ll have the opportunity to build great infrastructure. You can be as creative as you want as long as it creates a better product.
• You'll work on a modern and robust stack: Go, gRPC, Protobuf, Python, GraphQL, Typescript and React.
• You will team up with the founders to create a great product with your signature on it.
• We love open-source and will support you in the process of contributing to libraries we use or open-sourcing some of our work.
• You’ll join a company at an early stage and you will receive an attractive package containing salary and shares.
• You'll join an amazing team who loves food. Want to know who could be your future colleagues? Have a look here.