Knowledge Engineer

Vintti is a strategic staffing agency that enhances the competitiveness of US businesses. By connecting SMBs, startups, and firms with highly skilled Latin American professionals, we offer a cost-effective solution to talent acquisition. Our model allows companies to access top-tier expertise at rates that significantly reduce overhead costs, enabling businesses to allocate resources more efficiently and boost their bottom line.

A Knowledge Engineer is a professional dedicated to developing and managing knowledge-based systems, ensuring that information is captured, organized, and easily retrieved to support decision-making processes. They work at the intersection of information technology and subject matter expertise, drawing on advanced data modeling techniques and artificial intelligence to create systems that emulate human decision-making. Knowledge Engineers play a crucial role in transforming raw data into actionable insights, enhancing operational efficiency and enabling companies to leverage their collective intelligence effectively.

- Bachelor's degree in Computer Science, Information Systems, Artificial Intelligence, or a related field.
- 3+ years of experience in knowledge engineering or a similar role.
- Strong proficiency in programming languages such as Python, Java, or similar.
- Experience with knowledge representation frameworks like RDF, OWL, or similar.
- Demonstrable expertise in designing and implementing ontologies and taxonomies.
- Hands-on experience with natural language processing (NLP) techniques and tools.
- Proficiency in machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch).
- Familiarity with database systems (SQL, NoSQL) and data integration techniques.
- Solid understanding of model building and data analysis.
- Experience with automated reasoning systems and inferencing techniques.
- Proficient in using version control systems such as Git.
- Strong problem-solving skills and detail-oriented mindset.
- Excellent written and verbal communication skills.
- Ability to work collaboratively with cross-functional teams and stakeholders.
- Experience with enterprise knowledge management systems and tools.
- Capable of conducting data audits and ensuring data quality and integrity.
- Proven ability to document processes, standards, and technical procedures.
- Commitment to continuous learning and staying updated with industry trends.
- Experience in training and supporting end-users on technical tools.
- Self-motivated and able to work independently with minimal supervision.

- Gather and analyze large datasets to derive meaningful insights.
- Design and implement effective ontologies and taxonomies for knowledge representation.
- Collaborate with subject matter experts to capture and structure domain-specific knowledge.
- Develop and maintain a comprehensive knowledge base with up-to-date and accurate information.
- Create and deploy reasoning systems for inferring new knowledge from existing data.
- Integrate knowledge systems with enterprise applications and databases seamlessly.
- Develop and fine-tune NLP algorithms for improved information retrieval and extraction.
- Apply machine learning techniques to enhance the functionality and performance of knowledge systems.
- Conduct regular audits to maintain data integrity and report findings.
- Troubleshoot and resolve technical issues related to knowledge management tools.
- Document all processes, methodologies, and best practices related to knowledge engineering.
- Stay current with advancements in knowledge engineering and associated technologies.
- Perform user acceptance testing on developed knowledge systems and incorporate feedback.
- Train users on how to effectively utilize knowledge management tools and resources.

The ideal candidate for the Knowledge Engineer role is a highly analytical and innovative professional with a Bachelor's degree in Computer Science, Information Systems, Artificial Intelligence, or a related field, and at least three years of relevant experience. They possess strong proficiency in programming languages such as Python or Java, coupled with hands-on expertise in knowledge representation frameworks like RDF and OWL. Demonstrable experience designing and implementing ontologies and taxonomies is essential, along with a solid understanding of natural language processing (NLP) techniques and machine learning algorithms. The candidate is proficient in using tools like TensorFlow or PyTorch and has a deep understanding of both SQL and NoSQL database systems. They exhibit a meticulous attention to detail, ensuring data integrity and performing regular audits to maintain high standards. With excellent communication skills, both written and verbal, they can collaborate effectively with cross-functional teams and articulate complex technical concepts clearly. The candidate is adept at integrating knowledge systems with enterprise applications and is proficient in troubleshooting and resolving technical issues. They are self-motivated, driven, and capable of working independently while also being a collaborative team player. A proactive learner, they stay current with industry advancements, maintaining a commitment to continuous improvement and high ethical standards in data privacy and security. Their ability to translate technical knowledge into practical applications for end-users, combined with strong organizational skills and a commitment to exceptional results, sets them apart as the perfect fit for this role.

- Analyze complex data sets to extract insights and develop knowledge models.
- Design and implement knowledge representation systems, including ontologies and taxonomies.
- Collaborate with subject matter experts to identify and structure key information for various domains.
- Develop and maintain a knowledge base, including updating and curating content for accuracy and relevance.
- Create and deploy automated reasoning systems to infer new information from existing data.
- Integrate knowledge systems with other enterprise applications and databases.
- Develop and implement natural language processing (NLP) algorithms to enhance information retrieval and extraction.
- Utilize machine learning techniques to improve the accuracy and performance of knowledge systems.
- Conduct regular audits and quality checks of the knowledge base to ensure data integrity and consistency.
- Provide technical support and troubleshooting for knowledge management tools and platforms.
- Document processes, methodologies, and guidelines for knowledge engineering practices.
- Engage in continuous learning to stay updated with the latest advancements in knowledge engineering and related technologies.
- Perform user acceptance testing of knowledge systems and gather feedback for enhancements.
- Train and support end-users on effective use of knowledge resources and tools.

- Analytical mindset with the ability to interpret complex data
- Strong problem-solving skills with a meticulous attention to detail
- Excellent communication skills, both written and verbal
- Collaborative team player with the ability to work effectively with diverse groups
- Innovative thinker capable of developing creative solutions
- Self-motivated and driven, with the ability to work independently
- Strong organizational skills with the ability to manage multiple tasks simultaneously
- Technically adept with a deep understanding of programming and data analysis
- Proactive learner who stays current with industry standards and advancements
- Strong proficiency in knowledge representation and management techniques
- Proficient in machine learning and natural language processing methodologies
- Detail-oriented with a commitment to maintaining high standards of data integrity
- Efficient in troubleshooting and problem resolution for technical issues
- Capable of translating technical knowledge into practical applications for end-users
- Experience in conducting and analyzing user feedback to improve systems
- Enthusiastic about continuous learning and self-improvement
- Adaptable and flexible in a fast-paced, evolving environment
- Dedicated to high-quality work and achieving exceptional results
- Strong ethical standards with a commitment to data privacy and security
- Ability to articulate complex concepts in a clear and understandable manner

- Competitive salary range commensurate with experience
- Comprehensive health insurance (medical, dental, vision)
- Flexible working hours
- Remote work opportunities
- Generous paid time off (PTO) and holidays
- Retirement savings plan with employer match
- Professional development and training opportunities
- Tuition reimbursement program
- Employee wellness programs
- On-site gym and wellness facilities
- Collaborative and inclusive work environment
- Company-sponsored events and team-building activities
- Access to the latest tools and technologies
- Opportunities for career advancement and growth
- Stock options or equity participation plans
- Performance bonuses and incentives
- Membership to professional associations and conferences
- Employee assistance programs (EAP)
- Discounts on company products or services
- Relocation assistance for eligible positions