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Job Description & How to Apply Below
Job Summary:
We are looking for a motivated AI/ML Engineer to join our AI team. This is an exciting opportunity to work on projects at the cutting edge of generative AI—including large language models (LLMs), image generation, and multimodal AI. You’ll contribute to building, fine-tuning, and integrating GenAI solutions, primarily using Python and Google Cloud Platform (GCP).
Qualifications:
Education:
- Master’s degree in computer science, Engineering, Mathematics, or a related field.
Experience:
- Strong Python programming skills: familiarity with libraries such as Transformers, diffusers, or similar GenAI toolkits is a plus.
- Basic understanding of generative AI concepts (LLMs, agents, RAG, text-to-image, diffusion models, etc.).
- Interest or experience in using APIs and SDKs for LLMs (OpenAI, Gemini, Claude, or similar) and image generation (Imagen, Stable Diffusion, etc.).
- Familiarity with cloud platforms, especially Google Cloud Platform (GCP), or strong willingness to learn.
- Strong knowledge of Git and experience working with version control in a collaborative environment.
- Enthusiastic about GenAI, eager to learn modern engineering team practices, and able to work collaboratively.
Key Responsibilities:
- Assist in the development, evaluation, and fine-tuning of large language models (LLMs) and image generation models.
- Support the integration of GenAI models into our cloud-based workflows (GCP), including API usage and orchestration.
- Collaborate closely with engineering and data science team members on code reviews, feature development, and sprint activities.
- Use Git for version control, branching, merging, and code collaboration according to established workflows (pull requests, code reviews, etc.).
- Contribute data pipelines and maintain scripts in Python for GenAI applications.
- Conduct experiments, benchmark model performance, and assist in the analysis of results.
- Participate in maintaining project documentation and team knowledge sharing.
Working Conditions:
- Full-time.
- Limited travel may be required depending on team needs.
- Flexibility to operate in a global organization.
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