Machine Learning Engineer, Intapp
Knowledge and Reasoning
+ Variable compensation and equity
3-5 days a week in office
Cloud-based firm management software
Be an early applicant
Cloud-based firm management software
1001+ employees
Be an early applicant
+ Variable compensation and equity
3-5 days a week in office
1001+ employees
Company mission
To help professional and financial services firms run smarter.
Role
Who you are
- 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)
- 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
- Proficiency in Python and experience with data preprocessing, feature engineering, and model evaluation techniques specific to NLP tasks
- 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
- Excellent communication skills and the ability to work effectively with cross-functional teams
Desirable
- 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
- Hands-on experience working with vector databases (e.g., Weaviate, Milvus, ChromaDB etc)
- Experience in large scale and low latency solution design experience, modern methodologies and operating models, and familiarity with current MLOps best practices
- Proficiency in containerization and orchestration tools (e.g., Docker, Kubernetes) for scalable model deployment and version control systems (e.g., Git)
- 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 the job involves
- 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
- 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
- Build scalable machine learning models and own the machine learning lifecycle end-to-end from data exploration to model deployment and monitoring
- 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
- Collaborate with data scientists and engineers to deploy domain-specific machine learning services and applications in production environments
- Stay current with the latest research and technology, while sharing and communicating relevant knowledge with the rest of the organization
Our take
The global professional and financial service industries face unique operating challenges and regulatory requirements across their entire management lifecycle, from strategy to execution. Intapp provides end-to-end, cloud-based connected firm management, driving optimal outcomes by enabling enhanced collaboration and data access to fuel better decision-making.
The company’s suite of solutions has been enriched through acquisitions (Billstream, Repstor, One Place, DealCloud, and more) and strategic partnerships (Including Equilar and KPMG AG). Intapp powers more than 2,100 of the world’s premier private capital, investment banking, legal, accounting, and consulting firms to connect their most important assets: people, processes, and data.
Founded in 2000, the company went public in June 2021 and has since seen solid year-on-year growth. The company has made consistent, strong moves to remain competitive in the complex and ever-changing business environment, acquiring companies such as Transform Data International to boost its offering. Fresh from post-IPO funding, it's well set to remain a leading provider of purpose-built industry cloud solutions.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Company benefits
- Generous PTO, with Additional Companywide Paid Days Off to Allow Teams to Disconnect
- Medical Benefits
- Wellness Programs and Benefits Provided by Modern Health
- Paid Parental Leave and Adoptive Leave
- Flexible Work Environment
- Home Office Stipend
- Paid Volunteer Time Off and Donation Matching
- Co-Working Office Spaces
- Open Offices & Stocked Kitchens
- Women’s Interest Network
Company values
- At Intapp, we’ve built a company in which our core values are rooted in respect, deep care, and concern for each individual — a place where every employee is welcomed.
Company HQ
Ventura, Palo Alto, CA
Articles
Leadership
Thad Jampol
(CPO)Received their BS in Computer Science from the University of California, Los Angeles.
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