Artificial Intelligence Engineer

Vintti is revolutionizing remote staffing by prioritizing time zone alignment. We connect US-based SMBs, startups, and firms with Latin American professionals who work synchronously with US schedules. This approach ensures that businesses can maintain their usual workflows, conduct real-time meetings, and collaborate effectively without the typical challenges of working across disparate time zones.

An Artificial Intelligence (AI) Engineer is at the forefront of developing cutting-edge technologies that enable machines to perform tasks that typically require human intelligence. This role involves designing, building, and deploying AI models and systems that can analyze data, recognize patterns, and make decisions, often leveraging machine learning, deep learning, and natural language processing. AI Engineers collaborate with data scientists, software developers, and other stakeholders to implement AI-driven solutions that enhance business processes, improve customer experiences, and drive innovation across various industries.

- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or related field
- At least 3 years of experience in machine learning, data science, or a related area
- Proficiency in programming languages such as Python, R, or Java
- Experience with machine learning frameworks and libraries like TensorFlow, PyTorch, and scikit-learn
- Strong understanding of statistical methods and data analysis techniques
- Hands-on experience with data preprocessing, feature engineering, and data cleaning
- Proficiency in designing and implementing machine learning pipelines
- Experience with model development, testing, and deployment
- Ability to optimize and tweak algorithms for better performance and scalability
- Familiarity with version control systems like Git
- Experience with cloud platforms like AWS, Google Cloud, or Azure for deploying AI models
- Knowledge of database management systems and SQL
- Excellent problem-solving and debugging skills
- Strong written and verbal communication skills
- Ability to work collaboratively in a cross-functional team environment
- Familiarity with A/B testing and other validation techniques
- Up-to-date knowledge of advancements in AI and machine learning
- Understanding of ethical standards and data privacy regulations
- Ability to create and maintain comprehensive documentation
- Experience presenting technical concepts to non-technical stakeholders
- Ability to mentor junior team members and interns
- Strong project management and organizational skills

- Develop, test, and deploy machine learning models and algorithms.
- Collaborate with data scientists, software engineers, and product managers.
- Conduct data preprocessing, feature engineering, and data cleaning.
- Analyze and interpret complex datasets.
- Optimize algorithms for performance, efficiency, and scalability.
- Design and implement machine learning pipelines.
- Write and maintain code in Python, R, or Java.
- Utilize frameworks like TensorFlow, PyTorch, or scikit-learn.
- Monitor and evaluate the performance of deployed models.
- Implement A/B testing and validation techniques.
- Stay updated with advancements in AI and machine learning.
- Troubleshoot and debug issues in AI models.
- Create and maintain comprehensive documentation.
- Participate in code reviews.
- Present findings and updates to stakeholders.
- Explore new data sources, AI tools, and techniques.
- Ensure compliance with ethical standards and data privacy regulations.
- Provide mentorship to junior team members and interns.
- Develop custom AI tools and applications for specific needs.
- Communicate technical concepts to non-technical stakeholders.

The ideal candidate for the Artificial Intelligence Engineer role is a highly skilled professional with a Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field, complemented by at least three years of hands-on experience in machine learning, data science, or a related discipline. Proficiency in programming languages such as Python, R, or Java, along with substantial experience working with machine learning frameworks like TensorFlow, PyTorch, and scikit-learn, is essential. The candidate demonstrates a strong understanding of statistical methods and data analysis techniques and possesses hands-on experience in data preprocessing, feature engineering, and data cleaning. They are adept at designing and implementing efficient machine learning pipelines and have a proven track record of developing, testing, and deploying machine learning models at scale. The ideal candidate is skilled in optimizing algorithms for performance and scalability, familiar with version control systems like Git, and experienced with cloud platforms like AWS, Google Cloud, or Azure for deploying AI models. Outstanding problem-solving and debugging abilities, coupled with strong written and verbal communication skills, allow them to effectively collaborate within cross-functional teams. They possess excellent project management and organizational skills, with a keen eye for detail and a commitment to ethical standards and data privacy regulations. Exhibiting a proactive and self-motivated attitude, the candidate is not only passionate about artificial intelligence and machine learning but also dedicated to continuous learning and professional development. Their ability to simplify complex technical concepts for non-technical stakeholders, coupled with a knack for mentoring junior team members, makes them a valuable team player and leader, capable of handling multiple projects and priorities simultaneously with a high level of integrity and professionalism.

- Develop, test, and deploy machine learning models and algorithms for various AI applications.
- Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate AI solutions into products and services.
- Conduct data preprocessing, feature engineering, and data cleaning to prepare datasets for model training.
- Analyze and interpret complex datasets to identify patterns and insights critical to AI model performance.
- Optimize and tweak algorithms to improve performance, efficiency, and scalability.
- Design and implement machine learning pipelines, including data ingestion, processing, and training.
- Write and maintain code in programming languages such as Python, R, or Java.
- Utilize frameworks and libraries like TensorFlow, PyTorch, or scikit-learn for model development and deployment.
- Monitor and evaluate the performance of deployed models, ensuring they meet the required accuracy and reliability standards.
- Implement A/B testing and other validation techniques to assess the effectiveness of AI models.
- Stay updated with the latest advancements in AI and machine learning, incorporating cutting-edge technologies and methodologies into current projects.
- Troubleshoot and debug issues in AI models and improve them based on feedback and new data.
- Create and maintain comprehensive documentation for AI models, algorithms, and workflows.
- Participate in code reviews to ensure code quality and adherence to best practices.
- Present findings, results, and project updates to stakeholders and team members clearly and effectively.
- Explore and experiment with new data sources, AI tools, and techniques to enhance the capability of AI solutions.
- Ensure compliance with ethical standards and data privacy regulations in all AI-related tasks and projects.
- Provide mentorship and guidance to junior team members and interns in the AI engineering team.
- Develop custom AI tools and applications tailored to specific business needs or client requirements.
- Communicate technical concepts to non-technical stakeholders to facilitate understanding and decision-making.

- Strong analytical and problem-solving skills
- Innovative thinker and quick learner
- Detail-oriented and meticulous in work
- Excellent communication and interpersonal skills
- Proactive and self-motivated
- Adaptable to rapidly changing technology and environments
- Strong teamwork and collaboration capabilities
- Ability to handle multiple projects and priorities simultaneously
- Commitment to continuous learning and professional development
- Strong organizational and time management skills
- Ethical mindset with a strong understanding of data privacy
- Passionate about artificial intelligence and machine learning
- Ability to simplify complex technical concepts for non-technical audiences
- Effective mentor and leader
- High level of integrity and professionalism

- Competitive salary ranging from [insert range based on market standards]
- Comprehensive health, dental, and vision insurance
- Retirement savings plan with company match
- Flexible work hours and remote work options
- Generous paid time off, including vacation, sick leave, and holidays
- Professional development opportunities and educational assistance
- Access to the latest AI tools and technologies
- Collaborative and inclusive work environment
- Wellness programs, including gym memberships and mental health support
- Company-sponsored events and team-building activities
- Employee stock purchase plan or equity options
- Performance-based bonuses and incentives
- Relocation assistance if applicable
- Parental leave and family support benefits
- Commuter benefits and transportation reimbursement
- Opportunity to work on cutting-edge AI projects
- Regular training and workshops for skill enhancement
- Strong emphasis on work-life balance
- Mentorship and career growth programs