VeeRteq Solutions LLC
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 optimisation 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 modelling, 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
Bachelor's or Master's in Computer Science, Data Science, Engineering, Mathematics, or a 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 modelling, statistics, NLP, and machine learning algorithms.
Familiarity with CI/CD, MLOps, containerisation (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.
Certifications: AWS Solutions Architect, AWS Machine Learning Specialty, or equivalent.
Experience integrating Bedrock with real‑time applications and microservices.
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Engineering and Information Technology
Industries IT Services and IT Consulting
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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 optimisation 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 modelling, 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
Bachelor's or Master's in Computer Science, Data Science, Engineering, Mathematics, or a 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 modelling, statistics, NLP, and machine learning algorithms.
Familiarity with CI/CD, MLOps, containerisation (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.
Certifications: AWS Solutions Architect, AWS Machine Learning Specialty, or equivalent.
Experience integrating Bedrock with real‑time applications and microservices.
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Engineering and Information Technology
Industries IT Services and IT Consulting
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