Purple Drive
****************Local Preferred***********************
Role Overview
We are seeking a talented
Generative AI Engineer
with strong expertise in
Python
and modern AI/ML frameworks to design, build, and deploy
Generative AI-powered solutions . The ideal candidate will work on developing large language model (LLM) integrations, fine-tuning, and productionizing AI applications to accelerate digital innovation.
Key Responsibilities
Design, develop, and optimize
Generative AI models
for text, image, and multimodal use cases. Build and fine-tune
LLMs, Diffusion, and Transformer-based models
using
Python . Integrate AI solutions into scalable production systems with APIs and cloud services. Implement
MLOps practices
for model deployment, monitoring, and lifecycle management. Collaborate with product, data, and engineering teams to
deliver AI prototypes into production . Work with
vector databases (Pinecone, FAISS, Weaviate, etc.)
for retrieval-augmented generation (RAG). Leverage
cloud platforms (AWS, Azure, GCP)
for scalable AI infrastructure. Stay up to date with
emerging AI research
and proactively apply new techniques. Required Skills & Experience
5-8 years
of Python development experience. Hands-on expertise in
Generative AI, LLMs, Transformers, or Diffusion Models . Strong background in
PyTorch, TensorFlow, Hugging Face Transformers . Knowledge of
fine-tuning, prompt engineering, embeddings, and model optimization . Experience deploying models using
AWS Sagemaker, GCP Vertex AI, or Azure ML . Familiarity with
API development (FastAPI/Flask/Django)
for AI service integration. Solid understanding of
data preprocessing, pipelines, and system design . Nice to Have
Experience with
LangChain, LlamaIndex, or multi-agent AI frameworks . Knowledge of
Docker, Kubernetes (EKS/GKE/AKS)
for AI deployments. Familiarity with
observability and monitoring tools
for AI workloads. Exposure to
reinforcement learning, conversational AI, or multimodal AI . Soft Skills
Strong analytical and problem-solving mindset. Excellent communication and cross-functional collaboration skills. Ability to work independently and drive
AI projects from POC to production . Passion for
continuous learning and exploring cutting-edge AI technologies .
Role Overview
We are seeking a talented
Generative AI Engineer
with strong expertise in
Python
and modern AI/ML frameworks to design, build, and deploy
Generative AI-powered solutions . The ideal candidate will work on developing large language model (LLM) integrations, fine-tuning, and productionizing AI applications to accelerate digital innovation.
Key Responsibilities
Design, develop, and optimize
Generative AI models
for text, image, and multimodal use cases. Build and fine-tune
LLMs, Diffusion, and Transformer-based models
using
Python . Integrate AI solutions into scalable production systems with APIs and cloud services. Implement
MLOps practices
for model deployment, monitoring, and lifecycle management. Collaborate with product, data, and engineering teams to
deliver AI prototypes into production . Work with
vector databases (Pinecone, FAISS, Weaviate, etc.)
for retrieval-augmented generation (RAG). Leverage
cloud platforms (AWS, Azure, GCP)
for scalable AI infrastructure. Stay up to date with
emerging AI research
and proactively apply new techniques. Required Skills & Experience
5-8 years
of Python development experience. Hands-on expertise in
Generative AI, LLMs, Transformers, or Diffusion Models . Strong background in
PyTorch, TensorFlow, Hugging Face Transformers . Knowledge of
fine-tuning, prompt engineering, embeddings, and model optimization . Experience deploying models using
AWS Sagemaker, GCP Vertex AI, or Azure ML . Familiarity with
API development (FastAPI/Flask/Django)
for AI service integration. Solid understanding of
data preprocessing, pipelines, and system design . Nice to Have
Experience with
LangChain, LlamaIndex, or multi-agent AI frameworks . Knowledge of
Docker, Kubernetes (EKS/GKE/AKS)
for AI deployments. Familiarity with
observability and monitoring tools
for AI workloads. Exposure to
reinforcement learning, conversational AI, or multimodal AI . Soft Skills
Strong analytical and problem-solving mindset. Excellent communication and cross-functional collaboration skills. Ability to work independently and drive
AI projects from POC to production . Passion for
continuous learning and exploring cutting-edge AI technologies .