
Generative AI Developer
4 days ago
We are seeking a highly skilled
Generative AI (GenAI) Developer
with strong expertise in
Google Cloud Platform (GCP)
,
AI/ML frameworks
, and modern development practices. The ideal candidate will design, develop, and deploy scalable AI/ML solutions, with a focus on
Large Language Models (LLMs), NLP, and Generative AI applications
. You will collaborate with cross-functional teams to build intelligent, data-driven systems that drive business innovation.
Key Responsibilities
- Design, develop, and deploy
GenAI-powered applications
leveraging
LLMs, NLP, and multimodal AI models
. - Work on
end-to-end AI/ML lifecycle
, including data preprocessing, model training, fine-tuning, evaluation, and deployment. - Build and optimize solutions using
Google Cloud AI/ML services
(Vertex AI, AI Platform, BigQuery ML, TensorFlow on GCP). - Integrate
GenAI models with APIs, microservices, and enterprise applications
. - Develop
proof of concepts (POCs)
and production-ready solutions for various AI/ML use cases. - Collaborate with data engineers, product managers, and business stakeholders to
translate requirements into scalable AI solutions
. - Ensure compliance with
AI ethics, responsible AI practices, security, and data governance
. - Stay up to date with advancements in
AI, ML, and GenAI frameworks
to continuously innovate.
Required Skills & Qualifications
- Bachelor's or Master's degree in
Computer Science, Data Science, AI/ML, or a related field
. - Proven experience (X+ years) in
AI/ML development
, with a focus on
Generative AI
and
LLMs
(e.g., GPT, PaLM, LLaMA, Claude, etc.). - Strong expertise in
GCP services
– Vertex AI, Cloud Functions, BigQuery, Cloud Storage, Pub/Sub, AI/ML APIs. - Proficiency in
Python, SQL, and ML frameworks
(TensorFlow, PyTorch, Hugging Face Transformers). - Hands-on experience with
fine-tuning, prompt engineering, embeddings, and model deployment
. - Familiarity with
Docker, Kubernetes, CI/CD pipelines, and MLOps best practices
. - Strong understanding of
NLP, computer vision, or multimodal AI
concepts. - Excellent problem-solving, analytical thinking, and communication skills.
Preferred Qualifications
- Experience with
LangChain, RAG (Retrieval-Augmented Generation), and vector databases
(e.g., Pinecone, Weaviate, FAISS). - Knowledge of
data engineering pipelines
and cloud-native architectures. - Exposure to
AI security, ethical AI, and model interpretability
. - Certifications in
Google Cloud (Professional ML Engineer, Professional Data Engineer, or equivalent)
.
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