Machine Learning Engineer (m/f/d)
Location: Zürich, Switzerland
Position type: Full-time
Start date: By agreement
Are you looking to apply your strong machine learning (ML) / natural language processing (NLP) skills to real world problems, and help to keep companies around the globe transparent and accountable for their business conduct? Do you want to be part of a growing team of ML experts who deliver enterprise-scale applications that process and deliver real-time predictions directly to our ESG (environmental, social and governance) risk research flow, thereby reaching decision-makers using our data every day? Are you someone who prefers working for an agile, growing firm where you can make a real contribution and be involved in a variety of tasks, but without the uncertainty of a start-up?
If your answers are YES – then this is the perfect role for you!
As our new Machine Learning Engineer, you will join the Machine Learning team (part of Products division) and report to the Vice President of Research Technology, based in Zürich, Switzerland. You will be involved in the full machine learning life cycle within RepRisk, including design and experimentation, training and implementation, monitoring and operation. You will work on challenging ML problems primarily in natural language processing (NLP), including:
multi-lingual, multi-label and multi-class text classifications, event/topic clustering
entity detection and attribution
extractive and abstractive summarization
unique problems that call for a combination of sentiment and other analyses to solve
The resulting applications contribute directly to the data products on ESG risk that we serve to our clients and partners. You will be able to leverage our extensive labeled datasets in 23 languages, and there will be frequent opportunities to work on a broad range of technologies spanning from data processing and integration, core machine learning and NLP, to deployment and operation on a Unix environment within an increasingly cloud-based and container-based infrastructure (AWS, Kubernetes).
You will also contribute to the RepRisk machine learning knowledge base by creating and maintaining technical documentation, as well as to help sustain the high quality of our data by contributing to testing and quality assurance.
As the Machine Learning team grows, you will help us nurture an environment of innovation and cutting-edge NLP research and help maintain RepRisk’s position as an AI-first ESG risk data provider.
A graduate degree in computer science, data science or a related technical field with a strong foundation in machine learning, or equivalent practical experience.
Strong skills in Python, machine learning and deep learning libraries; working knowledge of Java would be a plus.
Experience with the full machine learning lifecycle (data gathering and preparation, model training, testing and selection, deploying, monitoring and re-training) of production-scale machine learning models in the industry setting. Familiarity with Docker and continuous integration and deployment (CI/CD) is a strong plus.
Interest and/or experience in natural language processing (NLP), knowledge of the latest NLP-specific approaches (trasformer-based NLP models e.g. BERT, RoBERTa, GPT-2 etc.), frameworks and libraries (spaCy, PyTorch).
Analytical and structured thinking, organized, solution-oriented, and efficient in execution.
Strong communication skills with a proficiency in English.
RepRisk is a rapidly-growing global company and a pioneer in the ESG data science field. Our goal is to make the world a better place by creating transparency in the business world – we are driving positive change via the power of data. We combine AI and machine learning with human intelligence to analyze public information and identify environmental, social, and governance risks. We serve as a reality check for how companies conduct their business around the world – do they walk their talk when it comes to human rights, labor standards, corruption, and environmental issues?
A shared mission to drive accountability and responsible behavior of companies, thus creating positive change
Opportunity to work with really interesting datasets on ESG risk, within an agile development ecosystem using state-of-the-art open-source techstack
A growing ML team that will support you to enhance your technical skills and knowledge; company support for continuous learning based on your interests and company needs (e.g. through relevant workshops, conferences)
Stability and structure of an established company without the red tape and excessive specialization of a large corporate; a flexible hardware policy (MacBook-friendly)
Flexible working hours and arrangements
An entrepreneurial, international, and dynamic work environment in a company that embraces diversity, because life would be boring if we were all the same!
Please note that we will only consider candidates with a valid work permit