Data Scientist (AWS Bedrock)

Job Title: Data Scientist AWS Bedrock Location: Chicago IL About the Role

We are seeking a highly skilled Data Scientist with hands-on experience in AWS Bedrock to design build and scale generative AI and machine learning solutions. The ideal candidate has a strong foundation in Python applied ML LLMs and cloud-native development with a focus on production-grade models and prompt engineering.

Key Responsibilities

• Develop fine-tune and deploy generative AI/LLM solutions using AWS Bedrock including foundation models such as Claude Llama and Titan.
• Build end-to-end ML workflows leveraging AWS services (S3 Lambda SageMaker Step Functions API Gateway DynamoDB RDS etc.).
• Design and implement prompt engineering strategies evaluation frameworks and model optimization techniques.
• Integrate Bedrock-powered AI capabilities into applications via APIs and SDKs.
• Collaborate with cross-functional teams to identify business problems and translate them into scalable AI/ML solutions.
• Perform data preprocessing feature engineering statistical modeling and experimentation.
• Develop scalable pipelines for model training inference and monitoring.
• Conduct A/B testing model performance evaluations and continuous improvement activities.
• Ensure adherence to security compliance and responsible AI best practices within AWS.
• Produce clear technical documentation reports and model explainability outputs.

Required Skills & Qualifications

• Bachelors or Masters in Computer Science Data Science Engineering Mathematics or related field.
• 3 7 years of experience as a Data Scientist or ML Engineer.
• Strong hands-on expertise with AWS Bedrock including provisioning model selection and orchestration.
• Advanced proficiency in Python including libraries such as NumPy pandas scikit-learn PyTorch or TensorFlow.
• Experience building and deploying ML/LLM applications in AWS.
• Knowledge of vector databases (e.g. Pinecone FAISS OpenSearch) and RAG pipelines.
• Strong grasp of data modeling statistics NLP and machine learning algorithms.
• Familiarity with CI/CD MLOps containerization (Docker) and version control (Git).
• Strong problem-solving abilities analytical mindset and communication skills.

Preferred Qualifications

• Experience fine-tuning LLMs using SageMaker or custom training pipelines.
• Prior work with multimodal models retrieval-augmented generation (RAG) or agent-based architectures.
• Certification: AWS Solutions Architect AWS Machine Learning Specialty or equivalent.
• Experience integrating Bedrock with real-time applications and microservices.

Key Skills
Laboratory Experience,Immunoassays,Machine Learning,Biochemistry,Assays,Research Experience,Spectroscopy,Research & Development,cGMP,Cell Culture,Molecular Biology,Data Analysis Skills
Employment Type : Full Time
Experience: years
Vacancy: 1