Machine Learning Engineer (Knowledge and Reasoning)

Machine Learning Engineer (Knowledge and Reasoning)

4 weeks ago Be among the first 25 applicants

Intapp, an established software company pioneering AI/ML platforms, is committed to driving profound transformations across global multi-billion-dollar industries, focusing primarily on the Professional and Financial Services Industries (from Legal, Accounting, Investment Banking, etc). Our cross-functional team is solving challenging problems and leveraging the latest technologies in AI, ML, and NLP. With our main AI and Data hub in Berlin, Germany, we are powered by a dynamic and innovative team bringing expertise in production-ready solutions and natural language processing solutions at scale.

We are seeking talented individuals passionate about technology and advancing AI and NLP technologies. Candidates should have specialized expertise in knowledge acquisition, representation, and application for AI, including a strong understanding of ontologies, knowledge graphs, vector databases, and semantic models, as well as hands-on experience with end-to-end machine learning lifecycles.

What you will do:

• Work on knowledge representation and NLP-driven projects, focusing on document intelligence to solve business use cases.
• Model knowledge from firmographic and demographic data, develop classification models, and apply information extraction techniques using knowledge frameworks.
• Build text generation models for content creation and summarization.
• Enhance recommendation and search algorithms by integrating structured knowledge for improved semantic search, ranking, and query understanding.

Additional responsibilities include:

• Design and develop systems leveraging semantic reasoning, ontology-based frameworks, and graph-based knowledge representations to extract insights from complex datasets.
• Build scalable machine learning models, owning the entire ML lifecycle from data exploration to deployment and monitoring.
• Evaluate production-level ML models through automated testing to assess performance, scalability, and reliability, selecting the most effective approaches.
• Collaborate with data scientists and engineers to deploy domain-specific ML services in production.
• Stay current with research and technology, sharing knowledge with the organization.

What you will need:

• 3+ years experience in building end-to-end systems leveraging machine learning and NLP, including large language models.
• Experience with knowledge representation and graph technologies, such as RDF, property graphs, ontologies, and tools like Protégé, SparQL, Neo4j, GraphDB.
• Proficiency in Python, data preprocessing, feature engineering, and model evaluation specific to NLP.
• Strong skills with cloud-based AI/big data solutions and NLP frameworks such as Transformers, spaCy, NLTK, Hugging Face, TensorFlow, or PyTorch.
• Excellent communication skills and ability to work with cross-functional teams.
• Fluency in English.

Nice to have:

• Experience integrating knowledge representation and graph systems into NLP pipelines.
• Hands-on experience with vector databases like Weaviate, Milvus, ChromaDB.
• Experience designing large-scale, low-latency solutions and familiarity with MLOps best practices.
• Proficiency with containerization (Docker, Kubernetes) and version control (Git).
• Experience with cloud platforms (AWS, Azure, Google Cloud) and REST APIs for deployment.

What you will gain at Intapp:

Our culture emphasizes accountability, responsibility, and growth in a positive, collaborative environment. We support professional success and work-life balance, offering competitive salaries, benefits, and opportunities for personal and professional development.

• Competitive salary, variable compensation, and equity.
• Generous parental leave, tuition reimbursement, family benefits, wellness programs, volunteer time off, and donation matching.
• Open, collaborative environment valuing your background and contributions.
• Impactful work at a growing public company.

Intapp is an equal opportunity employer and conducts background checks. We communicate only via official company channels and do not request financial information during the application process.