Natural Language Processing Engineer

Vintti stands at the forefront of economically advantageous staffing solutions for US businesses. By facilitating partnerships between American companies and Latin American professionals, we offer a pathway to reduced operational costs without sacrificing quality. Our approach enables businesses to reinvest savings into core areas, fostering growth and enhancing overall market competitiveness.

A Natural Language Processing (NLP) Engineer is a specialized software engineer focused on developing and implementing algorithms to enable computers to understand, interpret, and generate human language. Utilizing concepts from computational linguistics, machine learning, and data science, they transform unstructured text data into structured information. NLP Engineers work on tasks such as sentiment analysis, language translation, text summarization, and speech recognition, striving to bridge the gap between human communication and machine comprehension. Their expertise is pivotal in enhancing user experiences in applications like virtual assistants, chatbots, and advanced search engines.

- Bachelor's or Master's degree in Computer Science, Computational Linguistics, Natural Language Processing, or a related field
- Strong proficiency in programming languages such as Python or Java
- Experience with NLP libraries and frameworks like NLTK, SpaCy, Stanford NLP, and OpenNLP
- Proficiency in machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn
- Hands-on experience with deep learning models including RNNs, LSTMs, Transformers, BERT, GPT, etc.
- Solid understanding of linguistic concepts including syntax, semantics, and pragmatics
- Previous work experience in developing and shipping NLP solutions in production environments
- Demonstrated expertise in preprocessing and cleaning large text datasets
- Proven track record of optimizing machine learning models for performance and scalability
- Ability to design and conduct experiments to validate NLP models
- Experience working with big data technologies such as Hadoop, Spark, or similar
- Familiarity with cloud services like AWS, Google Cloud, or Azure for deploying NLP models
- Strong analytical skills and experience with data analysis tools
- Solid understanding of various NLP tasks such as sentiment analysis, named entity recognition, language translation, etc.
- Excellent communication skills, both verbal and written
- Ability to work collaboratively within cross-functional teams
- Experience in mentoring junior engineers or interns
- Strong problem-solving skills and a proactive approach to identifying and resolving issues
- Knowledge of software engineering best practices including code reviews, version control (Git), and CI/CD
- Commitment to staying updated with advancements in NLP and machine learning technologies
- In-depth understanding of data security and privacy standards, with a commitment to ethical use of data

- Develop and implement algorithms for processing natural language data
- Preprocess and clean large datasets for machine learning model training
- Optimize machine learning models using tools like TensorFlow, PyTorch, and scikit-learn
- Conduct validation experiments to test NLP model efficacy
- Integrate NLP models into applications with collaboration from data scientists and software engineers
- Analyze performance metrics to make iterative improvements on models
- Stay current with advancements in NLP and machine learning research
- Document methodologies, development processes, and results comprehensively
- Participate in code reviews, offering and receiving constructive feedback
- Scale NLP solutions to efficiently manage large datasets
- Develop methodologies for named entity recognition, sentiment analysis, and other NLP tasks
- Fine-tune pre-trained models like BERT and GPT for specific applications
- Automate data processing and analysis tasks through scripting
- Troubleshoot and debug NLP systems and applications
- Communicate technical findings to both technical and non-technical team members
- Mentor junior engineers and interns in NLP practices and techniques
- Collaborate with product teams to tailor NLP solutions to user requirements
- Ensure compliance with data security and privacy standards in NLP projects

The ideal candidate for the Natural Language Processing Engineer role is a highly skilled and experienced professional with a Bachelor's or Master's degree in Computer Science, Computational Linguistics, Natural Language Processing, or a related field. They possess strong proficiency in programming languages such as Python or Java and have extensive experience with NLP libraries and frameworks like NLTK, SpaCy, Stanford NLP, and OpenNLP. Demonstrating hands-on expertise with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn, the candidate is well-versed in deep learning models, including RNNs, LSTMs, Transformers, BERT, and GPT. They have a solid understanding of linguistic concepts and have a proven track record of developing and shipping NLP solutions in production environments. The candidate excels in preprocessing and cleaning large text datasets, optimizing models for performance and scalability, and designing experiments to validate these models. Familiar with big data technologies and cloud services, they bring strong analytical skills and a comprehensive understanding of various NLP tasks. Excellent communication skills enable them to articulate complex technical concepts clearly to diverse audiences, while their collaborative nature allows them to work seamlessly within cross-functional teams. They are a proactive problem solver with a keen eye for detail, demonstrating an unwavering commitment to continuous learning and staying updated with the latest advancements in NLP and machine learning. Their passion is matched by a strong sense of responsibility, ethical approach, and dedication to mentoring junior engineers. Adaptable to fast-paced environments, they are goal-oriented, efficient at task prioritization, and adept at managing multiple responsibilities. The ideal candidate is innovative, intellectually curious, and steadfast in upholding data security and privacy standards in all projects.

- Design and develop algorithms and models for processing natural language data
- Preprocess and clean large text datasets for use in training machine learning models
- Implement and optimize machine learning models using libraries such as TensorFlow, PyTorch, and scikit-learn
- Conduct experiments to test and validate the effectiveness of NLP models
- Collaborate with data scientists, software engineers, and other stakeholders to integrate NLP models into applications and systems
- Analyze model performance and make iterative improvements based on evaluation metrics
- Stay updated with the latest research and advancements in NLP and machine learning
- Document model development processes, results, and methodologies
- Participate in code reviews and provide constructive feedback to peers
- Optimize and scale NLP solutions to handle large volumes of data efficiently
- Develop methods for named entity recognition, sentiment analysis, language translation, and other NLP tasks
- Fine-tune pre-trained language models (e.g., BERT, GPT) for custom applications
- Write scripts and tools to automate data processing and analysis tasks
- Engage in troubleshooting and debugging of NLP systems and applications
- Communicate findings and progress to technical and non-technical team members
- Mentor and guide junior engineers and interns in NLP techniques and best practices
- Collaborate with product teams to understand user requirements and tailor NLP solutions accordingly
- Ensure the ethical use and compliance of data security and privacy standards in NLP projects

- Proactive problem solver with a hands-on approach
- Strong analytical thinker with keen attention to detail
- Excellent communicator, able to articulate complex technical concepts to both technical and non-technical stakeholders
- Highly collaborative team player who can work effectively within cross-functional teams
- Passionate about continuous learning and staying updated with the latest advancements in NLP and machine learning
- Strong sense of responsibility and commitment to producing high-quality, ethical work
- Demonstrated ability to mentor and guide junior team members
- Adaptable and flexible in a fast-paced, evolving environment
- Goal-oriented and capable of managing multiple tasks
- Innovative mindset, always looking for new ways to solve problems and improve processes
- High level of intellectual curiosity and interest in keeping up with industry trends
- Effective at prioritizing tasks and managing time efficiently
- Strong work ethic and dedication to meeting deadlines
- Ability to provide and receive constructive feedback gracefully
- Committed to upholding data security and privacy standards in all projects

- Competitive salary range
- Comprehensive health benefits including medical, dental, and vision insurance
- Flexible work hours
- Remote work options
- Generous paid time off and holidays
- Parental leave
- Professional development opportunities
- Reimbursement for relevant courses and certifications
- Access to cutting-edge tools and technologies
- Employee assistance programs
- Wellness programs and gym memberships
- Stock options or equity participation
- Retirement savings plan (e.g., 401(k) with company match)
- Company-sponsored events and social activities
- Collaborative and inclusive work environment
- Opportunities for career growth and advancement
- Dedicated time for research and innovation
- Mentorship programs and peer learning groups
- Regular performance reviews and feedback sessions
- Access to industry conferences and seminars
- Office perks such as free snacks, beverages, and ergonomic workstations
- Relocation assistance, if applicable