Generative AI Automation Engineer - Remote Job
Remote engineer who designs, builds, and deploys Generative AI–powered automation: fine-tuning and integrating models (GPT, Stable Diffusion, DALL-E), developing AI-driven workflows and APIs, wiring them into enterprise systems, and monitoring/optimizing them. Core stack is Python with TensorFlow/PyTorch/Hugging Face, cloud platforms, and Docker/Kubernetes.
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Ai engineering
- Posted
Skills
Must have
- Bachelor's or Master's degree in Computer Science, Engineering, or related field
- Strong programming skills in Python, with experience in TensorFlow, PyTorch, or Hugging Face
- Proficiency in designing and deploying machine learning models, particularly Generative AI
- Experience with automation tools (e.g., RPA, workflow orchestration tools)
- Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization (Docker, Kubernetes)
- Solid understanding of data structures, algorithms, and software design principles
- Strong analytical and problem-solving skills
- Excellent communication and teamwork abilities
Nice to have
- 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
Full 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.