Cognitive Computing Engineer

Vintti specializes in providing US companies with a financial edge through smart staffing solutions. We bridge the gap between American businesses and Latin American talent, offering access to a vast pool of skilled professionals at competitive rates. This approach enables our clients to scale their operations more efficiently, reduce hiring costs, and invest in growth opportunities without compromising on quality.

A Cognitive Computing Engineer specializes in designing, developing, and implementing systems that simulate human thought processes to solve complex problems. They leverage technologies such as artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) to create intelligent systems capable of understanding and interpreting vast amounts of data. This role requires a strong foundation in computer science, algorithms, and data structures, as well as proficiency in programming languages and tools relevant to AI and ML. Cognitive Computing Engineers collaborate with cross-functional teams to integrate cognitive solutions that optimize business processes, enhance decision-making, and drive innovation.

- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or related field.
- Strong background in machine learning, deep learning, and natural language processing.
- Proficiency in programming languages such as Python, Java, or C++.
- Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Familiarity with big data technologies (e.g., Hadoop, Spark) and data processing tools.
- Knowledge of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and on-premises deployment.
- Strong analytical and problem-solving skills with experience in statistical analysis and algorithm development.
- Experience with data visualization tools and techniques.
- Ability to work with large, complex datasets to extract meaningful insights.
- Excellent communication and collaboration skills to work effectively in a team environment.
- Proven track record of developing and deploying cognitive computing solutions in a professional setting.
- Knowledge of software development best practices, including version control, testing, and CI/CD.
- Experience with API development and integration.
- Strong documentation skills for models, algorithms, and tools.
- Ability to stay current with the latest advancements in AI, machine learning, and cognitive computing.
- Experience conducting research and experiments to innovate and improve methodologies.
- Ability to manage multiple projects and meet deadlines in a fast-paced environment.
- Strong organizational skills and attention to detail.
- Enthusiastic about learning new technologies and methodologies.

- Design and develop cognitive computing models to address complex problems.
- Analyze large datasets for model training and evaluation.
- Collaborate with cross-functional teams to refine and enhance algorithms.
- Implement and test cognitive solutions on various platforms.
- Optimize machine learning models for performance, scalability, and accuracy.
- Document cognitive computing models, algorithms, and tools.
- Conduct code reviews to maintain code quality and best practices.
- Integrate cognitive solutions with existing systems.
- Monitor and evaluate cognitive solution performance.
- Update models based on performance assessment.
- Stay informed of advancements in AI, machine learning, and cognitive computing.
- Provide technical support and guidance to team members and stakeholders.
- Conduct research to innovate and improve cognitive solutions.
- Participate in project meetings to discuss progress and challenges.
- Develop prototypes and proof-of-concepts for cognitive solutions.
- Prepare and present technical reports and findings to stakeholders.

The ideal candidate for the role of Cognitive Computing Engineer is a highly skilled individual with a Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field, who possesses a strong foundation in machine learning, deep learning, and natural language processing. They are proficient in programming languages such as Python, Java, or C++, and have hands-on experience with prominent machine learning frameworks and libraries like TensorFlow, PyTorch, or Scikit-learn. With a deep understanding of big data technologies and data processing tools, as well as familiarity with cloud computing platforms like AWS, Azure, or Google Cloud, they are adept at managing and analyzing large datasets to extract meaningful insights. The perfect candidate is an innovative thinker with a demonstrated ability to develop and deploy cognitive computing solutions in a professional setting, and they possess strong statistical analysis and algorithm development skills. They are detail-oriented, with excellent problem-solving abilities, and are known for their effective communication and collaboration skills, making them a valuable team player. Their enthusiasm for staying current with the latest AI and cognitive computing advancements, coupled with a resourceful and proactive approach, enables them to manage multiple projects and meet deadlines effectively in a fast-paced environment. With strong documentation skills, a commitment to quality, and a customer-centric mindset, they excel in creating high-quality, user-focused cognitive solutions.

- Design and develop cognitive computing models to solve complex problems using machine learning, natural language processing, and artificial intelligence techniques.
- Analyze large datasets to extract meaningful patterns and insights for model training and evaluation.
- Collaborate with data scientists, software engineers, and domain experts to refine algorithms and improve system performance.
- Implement, test, and validate cognitive solutions on cloud-based or on-premises platforms.
- Optimize machine learning models for performance, scalability, and accuracy.
- Develop and maintain documentation for cognitive computing models, algorithms, and tools used.
- Conduct regular code reviews to ensure code quality and adherence to best practices.
- Integrate cognitive computing solutions with existing systems and workflows.
- Monitor and evaluate the performance of cognitive solutions and update models as necessary.
- Keep up-to-date with the latest advancements in AI, machine learning, and cognitive computing technologies.
- Provide technical support and guidance to other team members and stakeholders.
- Conduct experiments and research to explore new methodologies and improve existing cognitive solutions.
- Participate in cross-functional meetings to discuss project progress, requirements, and challenges.
- Develop prototypes and proof-of-concepts to demonstrate the feasibility and potential impact of cognitive solutions.
- Prepare and present technical reports and findings to stakeholders and senior management.

- Innovative and forward-thinking mindset
- High levels of curiosity and enthusiasm for cognitive technologies
- Strong analytical and critical thinking skills
- Detail-oriented with a focus on precision and accuracy
- Excellent problem-solving abilities
- Effective communicator, both written and verbal
- Collaborative and team-driven
- Self-motivated and proactive
- Strong time management and organizational skills
- Adaptable and able to manage multiple tasks simultaneously
- Eagerness to learn and stay updated with emerging technologies
- Ability to work effectively under pressure and meet deadlines
- Strong work ethic and commitment to delivering high-quality solutions
- Empathetic and customer-centric with a focus on user experience
- Resourceful and capable of working independently
- Technically adept with a strong grasp of the latest AI and ML trends
- Open to feedback and continuous improvement

- Competitive salary range based on experience and qualifications
- Comprehensive health, dental, and vision insurance plans
- Retirement savings plan with company matching contributions
- Generous paid time off (PTO) and holiday schedule
- Flexible working hours and remote work options
- Professional development and continuing education opportunities
- Employee wellness programs and resources
- Access to the latest tools and technologies in AI and cognitive computing
- Collaborative, innovative, and inclusive work environment
- Opportunities for career growth and advancement within the company
- Annual performance bonuses and merit-based incentives
- Paid parental leave and family support benefits
- Tuition reimbursement for further education and certifications
- Employee recognition and reward programs
- On-site amenities such as fitness centers and recreational areas (if applicable)
- Membership discounts and access to industry-related conferences and events
- Transportation and commuter benefits
- Employee assistance program (EAP) for personal and professional support
- Stock options or equity grants (if applicable)