Company Description
What is our mission at CyberVadis? To provide enterprises with a cost-effective and scalable solution for third-party cybersecurity risk management.
We are an ambitious, agile and international team (located all around the world in 10 countries). Developed by EcoVadis 7 years ago (the world’s most trusted provider of business sustainability ratings), we are driven by the success of our clients and have a strong background and expertise to offer the best SaaS solution.
We believe that people do their best work when they’re given the freedom to thrive and grow. Thinking big, bringing a positive attitude, and taking full ownership are three characteristics that thread our team together.
Work hard, have fun and make a difference: Come join us!
The Role / Your Impact:
As a Senior AI/ML Engineer, you will play a pivotal role in shaping and building the future of our product.
- In our agile environment you will have the opportunity to work across the entire AI stack, contributing to everything from model research and development to production deployment and infrastructure management.
- You will have the autonomy and strategic influence to define our AI roadmap, design the core infrastructure, and build the intelligent backbone that will power our product for years to come.
- You will be empowered to research, design, and implement cutting-edge solutions, including advanced Retrieval-Augmented Generation (RAG) pipelines, agentic workflows, and knowledge graph-enhanced systems in a cloud environment.
- If you are a hands-on builder who thrives on variety and wants to have a major impact on a growing product, we encourage you to apply. We seek fast learners with a passion for technology, a commitment to quality, a proven track record in problem-solving and design, and strong interpersonal skills.
What You Will Do / Key Responsibilities:
- Architect from the Ground Up:
- Design and implement the end-to-end AI/ML architecture, making key decisions about data pipelines, model serving infrastructure, and technology stack selection.
- Select appropriate AI models, tools and frameworks based on performance metrics, cost-effectiveness, and specific use cases.
- Work closely with our software engineering team to ensure seamless integration of AI microservices into our broader application architecture.
- Build Scalable AI Services:
- Design, tune, evaluate, and deploy machine learning models to power our core features, including document intelligence, classification, and semantic search.
- Take ownership of the entire AI workflow, from data analysis and preparation of structured and unstructured datasets, data ingestion and model experimentation to deploying scalable, reliable AI-enhanced microservices in a cloud environment.
- Engineer and maintain robust, scalable microservices and APIs to serve our ML models in production, ensuring they integrate seamlessly with our existing application.
- Implement and manage CI/CD pipelines for automated model building, testing, validation, and deployment. You will ensure we can iterate on our models quickly and confidently.
- Write clean, maintainable, and well-tested code. You will be responsible for the quality and performance of the features you build, including monitoring them in production. - Solve Practical ML Problems:
- Apply your expertise in modern NLP and machine learning to solve the concrete challenges of understanding and processing cybersecurity documents.
- Implement both established and cutting-edge machine learning methods for content analysis, metadata extraction, content classification, and others.
- Architect and implement end-to-end RAG systems for question-answering and semantic search over our corpus of cybersecurity documents. This includes optimizing document chunking, generating high-quality embeddings, and fine-tuning retrieval strategies.
- Develop techniques to process and integrate information from text, tables, and visual elements within documents, potentially exploring multi-modal embedding and retrieval strategies.
- Incorporate advanced prompt engineering techniques to optimize the performance of Large Language Models (LLMs). Implement rigorous evaluation protocols to measure and improve model accuracy, relevance, and factuality.
- Establish Best Practices:
- As a foundational member of the team, you will participate in setting the standards for AI development, including coding practices, MLOps, model evaluation, and responsible AI principles.
- Conduct code reviews, mentor other engineers and promote best practices in model development and deployment.
- Share knowledge through presentations, workshops, and team discussions to support cross-functional learning.
- Research & Innovate:
- Stay at the forefront of NLP and document AI research, exploring emerging techniques like knowledge graph extraction and advanced RAG architectures to continuously enhance our platform's capabilities.
- Experiment with new technologies and approaches – we're looking for someone who isn't afraid of challenges and thinks outside the box.
- Collaborate & Communicate:
- Collaborate closely with the CTO and product leadership to translate high-level business goals into a concrete technical vision and AI roadmap. You will identify opportunities and drive the technical strategy for AI-powered features.
- Work closely with product leaders and other engineers to brainstorm new features, prototype innovative solutions, and translate business requirements into technical reality.
Requirements:
- 8+ years of professional software development experience, with a proven track record of designing and building scalable, production-grade systems.
- 5+ years of hands-on experience applying AI/ML techniques to build real-world products.
- Deep understanding of algorithms and data structures, practical knowledge of data science concepts and ML tooling.
- Expert-level programming skills and proficiency with common ML frameworks and libraries.
- A highly adaptable, problem-solving and result-oriented mindset with the ability to work independently and take ownership in a fast-paced and dynamic environment.
- Excellent communication skills and a collaborative spirit, with a genuine desire to be a key player on a small, high-impact team.
- Fluent English (you will communicate in English daily, both verbally and in writing)
What We Prefer:
- Strong fundamentals in computer science/math (a degree is fine, but we value your skills and experience more).
- Strong understanding of machine learning algorithms, deep learning, and statistical modeling.
- Strong experience in working with structured/unstructured data, ability to organize and classify training/evaluation datasets.
- Broad experience across the machine learning lifecycle: data preprocessing, model training and evaluation, and deployment in a cloud environment.
- Practical experience with NLP, including transformer models (e.g., BERT, GPT) and information retrieval techniques (e.g., RAG, semantic search).
- Theoretical and practical understanding of LLMs, transformer architectures, and fine-tuning techniques. You know their capabilities and limitations.
- Hands-on experience in Document AI / Intelligent Document Processing using traditional models and Generative AI.
- Knowledge of SQL and ability to extract insights from databases.
Nice to have:
- Master’s or Ph.D. in Computer Science, Data Science, Mathematics, Physics, or a related field.
- Experience with building AI systems "from scratch", demonstrating an ability to navigate ambiguity and make critical technical decisions with long-term impact.
- Knowledge of security and compliance considerations around AI (e.g., data leakage, model risks).
- Hands-on experience with cloud platforms (preferably Azure, including its AI/ML services, storage solutions, and container orchestration).
- Experience or strong interest in multi-modal models and knowledge graphs.
- Proven experience with building and managing CI/CD pipelines and MLOps workflows (using tools like Azure DevOps, GitHub Actions, etc.), deploying and managing machine learning models in the cloud.
- Experience in building and consuming APIs within a microservices architecture.
- Hands-on experience with SQL/NoSQL databases and data processing pipelines.
- Experience with delivering safe code to production, focusing on cybersecurity and resilience of the application and APIs.
What We Offer:
- Competitive salary and benefits package.
- Remote work options and flexible working hours.
- Actual impact on the choice and shape of solutions developed.
- Opportunities for professional growth and development.
- Training and conference budget.
- A collaborative, innovative work environment with an iterative agile approach.
Additional Information:
Location: Warsaw, Poland; Remote/Hybrid
Employment: B2B or contract of employment
Team: Engineering
Reports to: Engineering Team Leader
The Process:
1. Application: Submit your resume describing your experience and skills. A Polish work permit is required for this position.
2. Screening Interview: An initial screening call with our HR team.
3. Company Fit Interview: A discussion with the Engineering Leadership to assess your technical and cultural fit and to answer any questions you may have.
4. Home Assignment: A practical coding assignment to evaluate your technical skills, similar to the work you would do in this role.
5. Final Interview: A final, obligatory on-site technical interview with the team you would be working with to discuss your assignment and assess your fit.