Career Opportunity

Machine Learning Engineer

Location: Anywhere in Ukraine
The Company:

Our mission at Shelf is to enable all employees to instantly know more. Shelf is a highly awarded, innovative knowledge automation platform that revolutionizes how organizations curate and distribute company knowledge! With our powerful MerlinAI, Shelf helps organizations move from their difficult to use, legacy knowledge base to knowledge automation delivering answers on demand to employees with questions, to front-line staff interacting with prospects or customers, and to self-service interactions via your website. With many pre-built integrations, SDKs and APIs, Shelf’s open knowledge infrastructure is extensible and integrates seamlessly with enterprise applications to improve the customer experience and employee productivity.

We are experiencing rapid growth and quickly need to expand the engineering team globally to keep up with market demand. This is an incredible opportunity to join a rapidly expanding organization growing revenue at over 400% per year. We have successfully acquired dozens of large enterprises including Fortune 100 customers and always deliver a great customer experience. Check out our recent funding announcement!

The Role:
The R&D department plays a pivotal role in driving the company to disrupt the market. Our team strives for engineering excellence and agility in developing solutions. We use the latest advances in cloud, NLP, and ML fields to build services used by top enterprise companies and famous brands, including Glovo, HelloFresh, Herbalife, and Harvard Business Review.

As a Machine Learning Engineer, you’ll be responsible for designing and developing systems, training, and serving production-ready ML-driven models to solve the most challenging problems at the time. You have a real chance to impact thousands of users, influence product development, and work alongside experienced engineers and data scientists.

We’re looking for someone who has:
  • 2+ years of experience with a proven record in the ML and data analytics
  • Solid programming experience in Python
  • Strong English verbal and written communication
  • Understanding foundations of Machine Learning (e.g. supervised/unsupervised learning, classification, regression, validation)
  • Experience in development, deployment, optimization, and support of machine learning solutions
  • Experience with AWS (SageMaker, Lambda, SQS, SNS, DynamoDB, Step Functions, Batch, ECS, EC2)
    Experience with Container Services (Docker, Kubernetes, etc)
  • Experience working with large-scale unstructured and structured data sets and databases
  • Experience in building REST API services
It will be a plus if you have:
  • Understanding theoretical concepts of Recommendation Systems, NLP (language modeling, text classification, sequence classification, question answering, clustering, topic modeling)
  • Experience with ML frameworks and libraries: PyTorch, Scikit-Learn, HuggingFace, fastText, Gensim, numpy, pandas
  • Experience with data processing tools and frameworks (Apache Spark, Airflow, etc)
  • Model optimization and compression (distillation, pruning, quantization, etc)
You will:
  • Use the latest advances in cloud, NLP, and ML fields to build services used by top enterprise companies and famous brands, including Glovo, HelloFresh, Herbalife, and Harvard Business Review
  • Build APIs for ML services in a self-sufficient delivery team that ships code to production frequently
  • Develop technical designs once you’re more familiar with the overall architecture
  • Work closely with Product Managers to sketch out design requirements given technical constraints in the initial stage of feature development
  • Be responsible for the features you built and shipped to production
  • Utilize AWS services to build Infrastructure as a Code using Terraform
  • Regularly conduct code reviews of your teammates
  • Mentor more junior developers on your team
  • Contribute to improving overall engineering culture by sharing your unique experience, learnings, best practices, and patterns
What Shelf Offers:
  • Company Stock Options
  • Medical insurance
  • 19 days of paid vacation leave per year. Unlimited sick leaves
  • Hardware: MacBook Pro
  • Education: access to Udemy Business account, company library of books, other opportunities are discussed on an individual basis
  • Modern technical stack (stackshare.io/shelf/shelf). Develop open-source software (github.com/shelfio)

If you’re interested in working with us, please send your CV to join@shelf.io

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