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Contractual Natural Language Processing Jobs in Arizona

Stay up-to-date with the latest advancements in natural language processing and AI technologies. * Collaborate with cross-functional teams to integrate prompts into AI applications seamlessly.

Data Scientist

Tucson, AZ · On-site +1

$50K - $100K/yr

... natural language processing software. * Assisting in preparing written reports, data summaries, or presentation materials that describe analytical approaches and results for non-technical staff.

Data Scientist

Tucson, AZ · On-site +1

$74K - $172K/yr

... natural language processing software. * Contributing to written reports, data summaries, or presentation materials that describe analytical approaches and results for non-technical staff. Minimum ...

AI ML Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

Experience with Natural Language Processing NLP * Familiarity with geospatial data and mapping tools * Knowledge of Monte Carlo simulations and stochastic modeling * Experience with Git and CICD ...

AI Engineer

Phoenix, AZ · On-site

$50K - $112K/yr

... natural language processing tools like NLTK for text analytics and sentiment analysis - Implementing neural networks and deep learning methods for advanced AI applications - Managing data quality and ...

Avaya Engineer ( AI/ML )

Phoenix, AZ · On-site

$96K - $132K/yr

Hands-on experience with AI/ML and Natural Language Processing (NLP) * Experience working with GitHub , GitHub Actions , and CI/CD pipelines * Experience with Five9 Contact Center Platform

In-depth knowledge of natural language processing (NLP), machine learning (ML), and deep learning techniques. * Experience with popular conversational AI platforms and frameworks such as Dialogflow ...

Architect

Phoenix, AZ · On-site

$63 - $83/hr

... natural language processing, computer vision, or reinforcement learning. • Experience in working with large and complex data sets, and using cloud platforms, such as AWS, Azure, or Google Cloud ...

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Contractual Natural Language Processing information

What are some typical challenges faced by professionals working in contractual natural language processing roles?

Professionals in contractual NLP roles often encounter challenges such as quickly adapting to new project requirements, managing tight deadlines, and working with limited access to proprietary data or tools. Since contract positions may involve collaborating remotely with diverse teams, effective communication and self-motivation are crucial. Additionally, staying updated with the latest NLP techniques and ensuring high-quality deliverables despite project constraints are ongoing expectations. Successful contractors are proactive in clarifying client needs and flexible in adjusting to evolving priorities.

What is a contractual natural language processing specialist?

A Contractual Natural Language Processing (NLP) specialist is a professional who works on short-term or project-based contracts to develop, implement, and optimize systems that allow computers to understand and process human language. Their responsibilities often include building chatbots, developing text analytics tools, and improving machine translation systems. Unlike full-time employees, contractual NLP specialists typically work for a specific duration or on particular projects, offering flexibility to both employers and professionals. They usually possess expertise in linguistics, programming, and machine learning.

What are the key skills and qualifications needed to thrive as a contractual natural language processing specialist?

To thrive as a Contractual Natural Language Processing (NLP) Specialist, you need a strong background in computational linguistics, machine learning, and programming (typically Python), often supported by a relevant degree or equivalent experience. Familiarity with NLP frameworks like NLTK, spaCy, or Hugging Face Transformers, and experience with cloud computing platforms, are commonly required; certifications in data science or cloud technologies can also be beneficial. Exceptional problem-solving skills, adaptability, and effective communication help specialists collaborate with diverse teams and clearly convey complex findings. These competencies ensure that NLP solutions are robust, scalable, and aligned with client objectives in dynamic project-based environments.

What is the difference between Contractual Natural Language Processing vs Data Scientist?

AspectContractual Natural Language ProcessingData Scientist
CredentialsTypically requires degrees in linguistics, computer science, or related fields; certifications in NLP toolsRequires degrees in statistics, computer science, or related fields; certifications in data analysis or machine learning
Work EnvironmentOften project-based, working with NLP teams or vendors on language-specific tasksIn-house or consulting roles analyzing data, building models, and deriving insights
Industry UsageCommon in tech, legal, healthcare, and customer service sectors for language processing tasksUsed across industries for data analysis, predictive modeling, and decision support

Contractual Natural Language Processing specialists focus on language-specific tasks often on a contractual basis, while Data Scientists analyze data broadly to inform business decisions. Both roles require technical skills but differ in focus and work environment.

Is contractual natural language processing in demand?

Contractual natural language processing roles are in demand due to the growing use of AI and machine learning in industries such as technology, healthcare, and finance. Skills in NLP tools like Python, TensorFlow, and data annotation are highly valued, and the field offers opportunities for contract-based and project-specific work.
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GenAI with Chatbot

Donato Technologies, Inc

Phoenix, AZ • On-site

Other

Re-posted 16 days ago


Job description

GenAI with Chatbot
Phoenix, Arizona
Job description

We are seeking an experienced AI Architect to lead the design, development, and implementation of an advanced internal-facing assistant solution. The ideal candidate will have a strong background in architecture, product evaluation, and hands-on implementation experience with AI-powered assistants similar to Glean or Rogo.

Key Responsibilities:

Design and architect a scalable, secure, and efficient internal assistant solution using cutting-edge AI and natural language processing technologies

Develop proof-of-concepts and prototypes to validate architectural decisions

Lead the integration of the chatbot with internal systems, databases, and APIs

Collaborate with cross-functional teams to gather requirements and ensure alignment with business objectives

Implement best practices for AI model deployment, monitoring, and continuous improvement

Provide technical leadership and mentorship to the development team

Stay up-to-date with the latest advancements in AI, GenAI, and LLMs, incorporating innovative features into the chatbot architecture

Required Qualifications:

10+ years of experience in software development, with a focus on AI and machine learning

Proven experience architecting and implementing internal-facing AI chatbot solutions similar to Glean or Rogo

Strong hands-on experience with Python, LLMs, and Generative AI technologies

Deep understanding of natural language processing, sentiment analysis, and text generation techniques

Expertise in cloud platforms (AWS, Azure, or GCP) for AI model deployment and scaling

Experience with MLOps practices and tools for model lifecycle management

Strong problem-solving skills and ability to translate complex business requirements into technical solutions

Excellent communication skills to explain technical concepts to both technical and non-technical stakeholders

Skills
Skills

PRIMARY COMPETENCY : Cognitive Services PRIMARY SKILL : AI/ML (Artificial Intelligence & Machine Learning) Algorithms PRIMARY SKILL PERCENTAGE : 60 SECONDARY COMPETENCY : Cognitive Services SECONDARY SKILL : Web Frameworks for Python (Flask & Django) SECONDARY SKILL PERCENTAGE : 40