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Senior Natural Language Processing Engineer Jobs in Michigan

Senior .NET Developer (Contract)

Troy, MI

$51.75 - $68.25/hr

We are seeking a Senior .NET Developer (Contractor) to support the modernization of our enterprise ... g., natural language processing, predictive analytics, or generative AI features). * Provide ...

Large language models (LLMs) and generative AI applications, machine learning models, natural language processing (NLP), optimization and mathematical programming and recommendation systems. * Builds ...

Large language models (LLMs) and generative AI applications, machine learning models, natural language processing (NLP), optimization and mathematical programming and recommendation systems. * Builds ...

Large language models (LLMs) and generative AI applications, machine learning models, natural language processing (NLP), optimization and mathematical programming and recommendation systems. * Builds ...

Sr. Process Engineer

Reed City, MI · On-site

$92K - $119K/yr

... natural and grated cheeses, Breakstone's ® cottage cheese, Cracker Barrel ® , Black Diamond ® ... As a Senior Process Engineer in our Reed City, MI yogurt plant, you will take ownership of the ...

Sr. Process Engineer

Reed City, MI · On-site

$91K - $118K/yr

... Kraft natural and grated cheeses, Breakstone?s cottage cheese, Cracker Barrel, Black Diamond ... As a Senior Process Engineer in our Reed City, MI yogurt plant, you will take ownership of the ...

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Senior Natural Language Processing Engineer information

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

AspectSenior Natural Language Processing EngineerData Scientist
Required CredentialsAdvanced degree in CS, NLP, or related field; experience with NLP frameworksDegree in CS, statistics, or related; data analysis skills
Work EnvironmentDevelops NLP models, algorithms, and language-specific toolsAnalyzes data, builds predictive models, visualizes insights
Employer & Industry UsageTech companies, AI startups, research institutions focusing on language techVarious industries including finance, healthcare, marketing

While both roles require strong analytical skills and programming knowledge, Senior NLP Engineers specialize in language-specific models and algorithms, whereas Data Scientists focus on broader data analysis and predictive modeling across various data types.

What are some common challenges faced by Senior Natural Language Processing Engineers when deploying NLP models to production?

Senior NLP Engineers often encounter challenges such as ensuring model scalability, maintaining accuracy with real-world data, and addressing data privacy concerns. Deploying models at scale requires optimizing for speed and efficiency, as well as monitoring performance to handle domain shifts or unexpected inputs. Collaboration with DevOps and data engineering teams is crucial to integrate models seamlessly into existing pipelines and to ensure robust, maintainable solutions.

What does a Senior Natural Language Processing Engineer do?

A Senior Natural Language Processing (NLP) Engineer designs and implements advanced algorithms that enable computers to understand, interpret, and generate human language. They work on tasks such as text classification, sentiment analysis, machine translation, and conversational AI. In addition to developing NLP models, they often lead projects, mentor junior team members, and collaborate with data scientists, software engineers, and product managers to build and deploy language-based applications. Their expertise helps organizations leverage language data to solve complex problems and improve user experiences.

What are the key skills and qualifications needed to thrive as a Senior Natural Language Processing Engineer, and why are they important?

To thrive as a Senior Natural Language Processing Engineer, you need a deep understanding of machine learning, linguistics, and advanced programming skills in languages like Python, typically backed by a degree in computer science or a related field. Familiarity with NLP frameworks (such as spaCy, NLTK, or Hugging Face), cloud platforms, and experience with deep learning libraries like TensorFlow or PyTorch are crucial. Strong problem-solving abilities, effective communication, and the ability to work collaboratively in multidisciplinary teams are standout soft skills. These skills and qualities are essential for developing, deploying, and refining language-based AI solutions that meet complex business and user needs.
What are the most commonly searched types of Natural Language Processing Engineer jobs in Michigan? The most popular types of Natural Language Processing Engineer jobs in Michigan are:
What job categories do people searching Senior Natural Language Processing Engineer jobs in Michigan look for? The top searched job categories for Senior Natural Language Processing Engineer jobs in Michigan are:
What cities in Michigan are hiring for Senior Natural Language Processing Engineer jobs? Cities in Michigan with the most Senior Natural Language Processing Engineer job openings:
Generative AI Automation Engineer - Remote Job

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Ann Arbor, MI • On-site

Other

Re-posted 23 days ago


Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.