(Fluent English) ML Engineer

Location

Latvia

Outstaff Your Team

Job Description

Our spin-off product and team are looking for an inquisitive ML Engineer who loves to create cool products and solve difficult challenges, as well as develop new useful features.

Product:
A solution created to automate support (text communication) for popular CRM systems using ML. The product is now in production.

Team:

We already have an experienced CTO with a background in Data Science and Machine Learning, a Back-end Developer and a Digital Marketing Specialist.

Together we will:

Improve and maintain current solutions for support automation;
Develop new features after being fully familiar with the architecture;
Discuss the project strategy, brainstorm with the team.

Requirements

What you will need:

2.5+ years of commercial experience in Machine Learning (including NLP);
Experience working with transforming models (usage, re-training, fine tuning);
Experience with Deep Learning frameworks: Pytorch, Tensorflow;
Solid experience with Python, OOP, Rest API (Flask, Celery);
Experience with Docker and Docker-compose for effective containerization and deployment strategies;
Good knowledge of NLP tools and libraries: NLTK, Spacy, scikit-learn, GenSim;
Experience with Seq2Seq models;
Deep understanding of theoretical concepts Language modeling, Named Entity Recognition, text classification, clustering, topic modeling, embedding, ML metrics.

Would be a plus:

Full immersion in Machine Learning;
Good sense of humor 😊

Benefits

We offer:

Remote work in Ukraine or in a similar time zone;
Cozy startup atmosphere with stability from a holding company;
Compensation in USD;
Adequate, friendly management and no bureaucracy;
Plenty of interesting talks and communication with the team.

Advice from our career coach

As a potential applicant for the role of ML Engineer, it is essential to showcase your inquisitive nature, passion for creating innovative products, and problem-solving skills. Here are some specific tips to help you stand out:

Highlight your commercial experience in Machine Learning, especially in NLP, showcasing your ability to work with transforming models and deep learning frameworks like Pytorch and Tensorflow.
Demonstrate your proficiency in Python, OOP, and Rest API, along with experience in Docker and Docker-compose for effective containerization and deployment strategies.
Emphasize your knowledge of NLP tools and libraries such as NLTK, Spacy, and scikit-learn, and your experience with Seq2Seq models.
Showcase your deep understanding of theoretical concepts like Language modeling, Named Entity Recognition, text classification, clustering, topic modeling, and ML metrics.
Consider highlighting any additional experience in Machine Learning or a good sense of humor as these are mentioned as desirable traits in the job description.