Machine Learning Engineer (NLP)

Our mission at Netguru is to help entrepreneurs and innovators shape the world through beautiful software. We care about trust, taking ownership, and transparency. As a Certified B Corporation®, we offer a safe, inclusive and productive environment for all team members, and we’re always open to feedback. If you want to work from home and be a full-time employee, great! We want to create the right opportunities for you.

Hi! We are Netguru. We help entrepreneurs and innovators shape the world through beautiful software. We’re looking for people to join our team and build a culture based on trust, taking ownership, and transparency. We offer a safe, inclusive, and productive environment for all team members. We respect and want to build on our diversity. We are a workplace open to adaptations.

Our Machine Learning Engineers and Data Engineers help companies from the finance and insurance sectors to become more customer-centric. We use machine learning capabilities to improve processes that affect customer experience.

We believe that machine learning is still programming and all the best software development practices apply to it. Building reproducible machine learning workflows is in our DNA. We use tools like MLFlow, Quilt Data or Polyaxon. You can learn more about how we do it with Polyaxon and Quilt or listen to our engineer’s talk on reproducible machine learning.

At the same time, machine learning has its own unique research flavor which we always keep in mind. We conduct seminars with a quarterly theme in order to learn about the newest research advancements. Occasionally we publish our RnD work. You can read our recent neural style transfer paper here. Join our team to contribute to the AI transformation!

What's in it for you?

• We focus on the finance and insurance sectors with use cases such as recommender systems, churn prediction, and applications of NLP to customer support
• We conduct seminars to learn about new research papers
• ML-Ops are very close to our heart. We use MLFlow for running reproducible ML pipelines
• We know that deep learning is computationally expensive. We use GCP and dedicated servers with GPUs
• We encourage our team to share knowledge and experience at external conferences
• We aim to apply our own research to commercial products
• We own building machine learning systems - from design with Machine Learning Canvas, through PoC, to implementation of production-ready solutions
• We work on our models iteratively; we start from simple baselines and avoid waterfall plans for huge ML systems
• We closely cooperate with a cross-functional team of great software engineers and product designers.

Requirements

Must-haves:

• Hands-on knowledge of Python,
• At least 1 year of practical experience in Machine Learning, using Python (academia or industry),
• Solid understanding of the theoretical concepts behind Machine Learning,
• Solid knowledge of machine learning workflow best practices,
• Familiarity with scientific and machine learning libraries such as:
  • NumPy
  • Pandas
  • Scikit-learn
• Familiarity with at least one of the following Deep Learning libraries:
  • Keras
  • Tensorflow
  • PyTorch
• Familiarity with at least one of the following NLP libraries:
  • spaCy
  • NLTK
  • Hugging Face transformers
  • Gensim
  • Spark NLP.
• Familiarity with at least three of the following NLP tasks:
  • Sentiment analysis
  • Machine Translation
  • Question Answering
  • Text Summarization
  • Named Entity Recognition
• Familiarity with theory behind transformers and language models (BERT, RoBERTa, XLNet, ELECTRA, etc.)
• Solid knowledge of data structures, object-oriented programming, and software engineering principles,
• Very good command of written and spoken English (CEFR B2+), Polish not required,
• Experience of co-operating with foreign clients and working in the Agile way.

Nice-to-haves:

• Practical experience in at least one of following:
  • Amazon Web Services (AWS) and Docker,
  • Kaggle track record,
  • GitHub / GitLab open source repository with sample ML solution that you prepared
  • Experience in deploying machine learning models to production,
  • Know Scrum and Agile methodologies.

Benefits

Perks & benefits:

• Access to the WorkSmile platform offering benefits adapted to your preferences:
  • Multisport card,
  • Private health insurance package,
  • Life insurance,
  • And hundreds of other options to choose from 15 categories (shopping, leisure, travel, food, etc.)
• Support for your growth - a book budget and a head/manager’s budget available to every employee,
• Discounts on Apple products,
• One-time 1000 PLN home office bonus,
• Home office equipment sharing option,
• Various internal initiatives: webinars, knowledge sharing sessions, internal conferences.

We are just getting started 🚀 Ready to face the challenge?

Click “apply now” button and join Netguru team!

Not interested in long-term cooperation? Join the Netguru Talent Marketplace and have access to various project-based opportunities. Get a gig and collaborate with different companies and industries. Have a possibility to not only gain more experience but also develop a variety of skills you didn't even know you had. Work the way you like, on your terms, with no strings attached.