Junior Research Engineer Machine Translation

A hybrid work model requires 1 day a week in the office (Warsaw).

At Allegro were building the future of ecommerce and language is a key part of that vision.  The Machine Learning Research Lab provides cuttingedge AI solutions specifically designed for the unique challenges of ecommerce. Within the Lab the Language Intelligence area focuses on making international platforms seamless for both buyers and sellers.  Were developing an inhouse Machine Translation (MT) system that goes beyond generic solutions accurately handling the nuances of ecommerce language and scaling efficiently.  Learn more about our work at the Role:

We are seeking a passionate and talented Research Engineer to join our Machine Translation team. You will be a key contributor to our efforts in building a stateoftheart MT system specifically tailored for the Allegro ecommerce marketplace. This role offers a unique opportunity to work on challenging research problems develop cuttingedge MT technology for a wide range of language pairs and see your work directly impact millions of users. Youll be contributing to making our platform accessible to an audience of nonPolish speakers.

Why is it worth working with us

• Impact: Being a part of the Machine Learning Research team you will be responsible for bringing to production research solutions for Allegro.

• Innovation: Were not just using offtheshelf solutions. Youll be working on novel approaches to machine translation leveraging stateoftheart machine learning methods and contributing to the advancement of the field. This includes exploring and integrating cuttingedge solutions based on commercial LLMs.

• Scale: You will be responsible for creating the productiongrade ML models supporting the development team in correct implementation: meeting technical and performance requirements.

• Collaboration: Youll be part of a team of experienced researchers and engineers fostering a culture of knowledge sharing and continuous learning. Your support will be needed both at the technical (e.g. what architecture will be appropriate for the domain) and bestpractices level (e.g. building data sets modeling metrics implementation of the MLbased solutions to the production) .

• Growth: To apply stateoftheart solutions you will stay up to date with the scientific progress. You will deepen your knowledge by reading the latest papers in your domain and sharing the knowledge with the research teams operating in Allegro. You will have the possibility to participate in scientific conferences visiting venues where the latest discoveries are presented developing your scientific career as well as Allegros presence in the science community.

In your daily work you will handle the following tasks:

• Research: Explore identify and implement stateoftheart neural machine translation models and techniques. Conduct thorough literature reviews to find the most promising approaches for specific problems. This includes investigating and evaluating the potential of commercial LLMs (e.g. ChatGPT Gemini) for machine translation tasks and developing innovative solutions leveraging these technologies.

• Model Development: Train evaluate and finetune machine learning models. Develop and refine prompting strategies for LLMs to optimize their performance for ecommerce translation.

• Data Analysis: Work with large datasets ensuring data quality and developing strategies for data augmentation and improvement.

• Collaboration: Work closely with other researchers and software engineering teams to integrate your models into production systems. Participate in the code review process.

• Continuous Learning: Stay on top of the latest advancements in machine translation and large language models by reading research papers attending conferences (virtually or in person) and participating in internal seminars. Prepare and deliver presentations.

• Production Support: Contribute to the preparation of productiongrade machine translation models and provide support to the development team during implementation.

• Quality Focus: Contribute to the development and application of automatic quality estimation models and work with human evaluators to continuously improve translation quality.

What we offer:

• Welllocated office (with fully equipped kitchens and bicycle parking facilities) and excellent working tools (heightadjustable desks interactive conference rooms)

• Annual bonus up to 10 of the annual salary gross (depending on your annual assessment and the companys results)

• A wide selection of fringe benefits in a cafeteria plan you choose what you like (e.g. medical sports or lunch packages insurance purchase vouchers)

• English classes that we pay for related to the specific nature of your job

• Working in a team you can always count on we have on board topclass specialists and experts in their areas of expertise

• A high degree of autonomy in terms of organizing your teams work; we encourage you to develop continuously and try out new things

• Hackathons team tourism training budget and an internal educational platform MindUp (including training courses on work organization means of communications motivation to work and various technologies and subjectmatter issues)

• If you want to learn more check it out

We are looking for people who have:

• Bachelors or masters degree in Computer Science Computational Linguistics Artificial Intelligence or a related field. Strong candidates nearing completion of their degree will also be considered

• Solid understanding of machine learning fundamentals particularly in the area of Natural Language Processing (NLP)

• Experience with ML  frameworks (e.g.  PyTorch transformers pandas)

• Programming proficiency in Python

• Strong analytical and problemsolving skills

• Demonstrated experience with prompting techniques and AI engineering for large language models (LLMs). Understanding of how to effectively interact with and leverage the capabilities of commercial LLMs

Bonus Points:

• Experience with machine translation models

• Experience with sequencetosequence models

• Familiarity with ecommerce data

• Contributions to opensource projects or publications in relevant conferences/journals

• Experience with utilizing LLMs in production environments

• Prior experience in running largescale computation on cloud platform (GCP Azure) 

• Prior experience in using LLMs for synthetic data generation/solving business problems

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Remote Work :

No

Employment Type :

Fulltime