Design, develop, and deploy AI/ML models on AWS using SageMaker, Bedrock, and related services
Build LLM-based applications and fine-tune models for domain-specific use cases
Implement RAG (Retrieval-Augmented Generation) pipelines with vector databases such as OpenSearch, Pinecone, or FAISS
Develop production-ready ML pipelines leveraging AWS services including Lambda, Step Functions, S3, and DynamoDB
Integrate ML models into real-world applications in collaboration with cross-functional teams
Ensure AI solutions align with best practices in security, compliance, and cost optimization
Stay current with the latest advancements in Generative AI, prompt engineering, and model optimization
Requirements
10-15 Years of experience
Strong expertise in AWS AI/ML stack: SageMaker, Lambda, Step Functions, S3, DynamoDB, etc.
Proven experience with Generative AI models (GPT, Claude, Mistral, LLaMA, etc.) and fine-tuning techniques
Hands-on programming experience with Python, TensorFlow, PyTorch, and Hugging Face
Knowledge of vector databases and embedding models
Experience in building secure, scalable AI solutions on AWS
Familiarity with MLOps practices, CI/CD pipelines, and cloud automation
Strong analytical and problem-solving skills with the ability to work in a fast-paced environment
Good to Have: Experience with LangChain, Prompt Engineering, and RAG techniques
Understanding of data governance, AI ethics, and responsible AI practices
AWS Certifications: Machine Learning Specialty / Associate or other relevant AI certifications
Benefits
Startup culture with opportunity to grow
Performance bonuses
Company stock options
Health, dental and vision insurance plans
Pursue growth and learning with career development expenses
Volunteer and support education for kids & skills development for adults
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
AI/ML modelsLLM-based applicationsRAG pipelinesvector databasesproduction-ready ML pipelinesGenerative AI modelsfine-tuning techniquesPythonTensorFlowPyTorch