Machine Learning Engineer (Knowledge and Reasoning)

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 who are passionate about technology and for advancing AI and NLP technologies. Candidates should have specialized expertise in the acquisition, representation and application of knowledge for AI. This includes 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:

You will work on knowledge representation and NLP-driven projects, focusing on document intelligence to solve business use cases. This includes modeling knowledge from firmographic and demographic data, developing classification models, and applying information extraction techniques using knowledge frameworks. You will also build text generation models for content creation and summarization and enhance recommendation and search algorithms by integrating structured knowledge for improved semantic search, ranking, and query understanding.

In addition:

1. Design and develop systems that leverage semantic reasoning, ontology-based frameworks, and graph-based knowledge representations to extract, structure, and derive insights from complex datasets.
2. Build scalable machine learning models and own the machine learning lifecycle end-to-end from data exploration to model deployment and monitoring.
3. Evaluate production-level machine learning models through automated scientific testing to assess performance, scalability, and reliability, selecting the most effective approaches based on evaluation results.
4. Collaborate with data scientists and engineers to deploy domain-specific machine learning services and applications in production environments.
5. Stay current with the latest research and technology, while sharing and communicating relevant knowledge with the rest of the organization.

What you will need:

1. Experience in building end-to-end systems that leverage machine learning and natural language processing (NLP) technologies, including large language models (typically 3+ years experience).
2. Experience with knowledge representation and graph-based technologies, such as with knowledge graphs (RDF, property graphs) and/or ontologies. Also includes familiarity with tools, frameworks and graph databases such as Protégé, SparQL, Ontology API, Neo4j, GraphDB etc.
3. Proficiency in Python and experience with data preprocessing, feature engineering, and model evaluation techniques specific to NLP tasks.
4. Strong technical skills with cloud-based AI & big data solutions, and familiarity with NLP frameworks and tools such as Transformers, spaCy, NLTK, Hugging Face, and TensorFlow or PyTorch.
5. Excellent communication skills and the ability to work effectively with cross-functional teams.

Nice to have:

1. Experience in integrating knowledge representation and graph-based technologies systems into NLP pipelines and leveraging graph-based structures for enhanced data insights is a plus.
2. Hands-on experience working with vector databases (e.g., Weaviate, Milvus, ChromaDB etc).
3. Experience in large scale and low latency solution design experience, modern methodologies and operating models, and familiarity with current MLOps best practices.
4. Proficiency in containerization and orchestration tools (e.g., Docker, Kubernetes) for scalable model deployment and version control systems (e.g., Git).
5. Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for infrastructure management and knowledge of RESTful APIs for integrating and deploying ML models in production systems.

What you will gain at Intapp:

Our culture at Intapp emphasizes accountability, responsibility, and growth. We support each other in a positive, open atmosphere that fosters creativity, approachability, and teamwork. We’re committed to creating a modern work environment that’s connected yet flexible, supporting both professional success and work-life balance. In return for your passion, commitment, and collaborative approach, we offer:

1. Competitive base salary plus variable compensation and equity.
2. Generous paid parental leave, including adoptive leave.
3. Traditional comprehensive benefits, plus:
4. Generous Paid Time Off.
5. Tuition reimbursement plan.
6. Family Formation benefit offered by Carrot.
7. Wellness programs and benefits provided by Modern Health.
8. Paid volunteer time off and donation matching for the causes you care about.
9. Opportunities for personal growth and professional development supported by a community of talented professionals.
10. An open, collaborative environment where your background and contributions are valued.
11. Experience at a growing public company where you can make an impact and achieve your goals.
12. Open offices and kitchens stocked with beverages and snacks.

#LI-MT2

Intapp provides equal employment opportunities to all qualified applicants and will make hiring decisions without regard to race, color, sex, sexual orientation, gender identity or expression, religion, national origin or ancestry, age, disability, marital status, pregnancy, protected veteran status, protected genetic information, political affiliation, or any other characteristic protected by federal, state or local laws. All offers are contingent upon passing a criminal history and other background checks if applicable to the position.

Please note: Intapp will not hire through text message, social media, or email alone. We will never extend a job offer unless you have been contacted directly by an Intapp recruiter and have participated in the interview process which will generally consist of 3 or more virtual or in person meetings. Please note that Intapp only uses company email addresses, which contain “@intapp.com” or “@dealcloud.com” to communicate with candidates via email. Intapp will never ask for financial information of any kind or for any payment during the job application process. We post all legitimate job openings on the Intapp Career Site at https://www.intapp.com/working-at-intapp/. If you believe you were a victim of such a scam, you may contact your local authorities. Intapp is not responsible for any claims, losses, damages, or expenses resulting from scammers.

Company:

Intapp

Qualifications:

Language requirements:

Specific requirements:

Educational level:

Level of experience (years):

Senior (5+ years of experience)

Tagged as: Big Data, Germany, Industry, Information Extraction, Language Modeling, NLP