Solid understanding of data structures, algorithms, and software design principles. * Strong ... Familiarity with prompt engineering and fine-tuning Generative AI models. * Knowledge of MLOps ...
Solid understanding of data structures, algorithms, and software design principles. * Strong ... Familiarity with prompt engineering and fine-tuning Generative AI models. * Knowledge of MLOps ...
Solid understanding of data structures, algorithms, and software design principles. * Strong ... Familiarity with prompt engineering and fine-tuning Generative AI models. * Knowledge of MLOps ...
Solid understanding of data structures, algorithms, and software design principles. * Strong ... Familiarity with prompt engineering and fine-tuning Generative AI models. * Knowledge of MLOps ...
Solid understanding of data structures, algorithms, and software design principles. * Strong ... Familiarity with prompt engineering and fine-tuning Generative AI models. * Knowledge of MLOps ...
Solid understanding of data structures, algorithms, and software design principles. * Strong ... Familiarity with prompt engineering and fine-tuning Generative AI models. * Knowledge of MLOps ...
Solid understanding of data structures, algorithms, and software design principles. * Strong ... Familiarity with prompt engineering and fine-tuning Generative AI models. * Knowledge of MLOps ...
Solid understanding of data structures, algorithms, and software design principles. * Strong ... Familiarity with prompt engineering and fine-tuning Generative AI models. * Knowledge of MLOps ...
Solid understanding of data structures, algorithms, and software design principles. * Strong ... Familiarity with prompt engineering and fine-tuning Generative AI models. * Knowledge of MLOps ...
Solid understanding of data structures, algorithms, and software design principles. * Strong ... Familiarity with prompt engineering and fine-tuning Generative AI models. * Knowledge of MLOps ...
Solid understanding of data structures, algorithms, and software design principles. * Strong ... Familiarity with prompt engineering and fine-tuning Generative AI models. * Knowledge of MLOps ...
Solid understanding of data structures, algorithms, and software design principles. * Strong ... Familiarity with prompt engineering and fine-tuning Generative AI models. * Knowledge of MLOps ...
Solid understanding of data structures, algorithms, and software design principles. * Strong ... Familiarity with prompt engineering and fine-tuning Generative AI models. * Knowledge of MLOps ...
Solid understanding of data structures, algorithms, and software design principles. * Strong ... Familiarity with prompt engineering and fine-tuning Generative AI models. * Knowledge of MLOps ...
Python-AI ML (GenAI) Senior Engineer
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Python-AI ML (GenAI) Senior Engineer
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Lead AI Software Engineer
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Epiq is seeking a highly skilled Lead AI Software Engineer to join our Operations Engineering team ... algorithms. * Excellent communication skills and ability to present technical concepts to non ...
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Software and AI/ML Developer
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You'll research and implement advanced algorithms that haven't been solved elsewhere. Direct ... and AI/ML Developer position? Core responsibilities include: * Design/architect, develop, test ...
Quick apply
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Senior AI Engineer - SFL Scientific
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Senior AI Engineer - SFL Scientific
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As a Prompt Engineer, you will be a key member of our AI development team, responsible for designing and developing high-quality prompts that drive our AI models and algorithms. Your expertise in ...
Quick apply
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Senior / Staff ML Onboard Optimization Engineer
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Ai Algorithm Engineer information
What are some common challenges AI algorithm engineers face when deploying models to production environments?
What is the difference between Ai Algorithm Engineer vs Data Scientist?
| Aspect | Ai Algorithm Engineer | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's or Master's in CS, AI, or related fields; knowledge of algorithms and programming | Bachelor's or Master's in CS, Statistics, or related fields; strong analytical skills |
| Work Environment | Develops and optimizes AI algorithms, often in R&D or product teams | Analyzes data, builds models, and provides insights for business decisions |
| Industry Usage | Tech companies, AI startups, research institutions | Finance, healthcare, marketing, tech firms |
While both roles require strong technical skills and a background in data or algorithms, Ai Algorithm Engineers focus on designing and improving AI algorithms, whereas Data Scientists analyze data to generate insights and build predictive models. The roles often overlap but serve different primary functions within organizations.
What are the key skills and qualifications needed to thrive as an AI algorithm engineer?
What is an AI algorithm engineer?

Full-time
Re-posted 15 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.
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Integrate pre-trained models or build custom models for specific use cases.
Automation Design and Development:
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Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.
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Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.
Data Management:
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Collect, preprocess, and analyze large datasets for training and validating AI models.
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Ensure data privacy and compliance with regulatory requirements during data handling.
System Integration:
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Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.
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Build and maintain pipelines for real-time AI inference and automation.
Monitoring and Optimization:
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Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.
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Optimize models and processes based on performance metrics and user feedback.
Research and Innovation:
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Stay updated with the latest advancements in Generative AI and automation technologies.
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Identify opportunities for implementing cutting-edge AI solutions to address business challenges.
Documentation and Collaboration:
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Document technical designs, workflows, and implementation strategies.
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Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.
Required Qualifications:
-
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
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Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.
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Proficiency in designing and deploying machine learning models, particularly in Generative AI.
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Experience with automation tools (e.g., RPA, workflow orchestration tools).
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Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).
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Solid understanding of data structures, algorithms, and software design principles.
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Strong analytical and problem-solving skills.
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Excellent communication and teamwork abilities.
Preferred Qualifications:
-
Experience with NLP, image generation, or multimodal AI models.
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Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.
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Familiarity with prompt engineering and fine-tuning Generative AI models.
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Knowledge of MLOps practices for deploying and maintaining AI solutions.
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Previous experience in automation or workflow optimization projects.
Why Join Us?
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Work with cutting-edge Generative AI technologies.
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Collaborate with a team of forward-thinking innovators.
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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.
About EnthuZiastic
Sourced by ZipRecruiter
Industry
E-learning
Company size
11 - 50 Employees
Headquarters location
San Jose, CA, US
Year founded
2020