Data Science/MLOps Engineer

About the role

We are seeking a highly skilled Senior Engineer with strong expertise in Python, Data Science, AI/ML, and AWS cloud technologies, along with hands-on experience in Terraform. The role involves building scalable data-driven and AI/ML solutions, leveraging foundation models and generative AI services, and contributing to cloud infrastructure automation and best engineering practices.

Responsibilities

• Design, develop, and maintain Python-based applications, data pipelines, and AI/ML solutions.
• Build, train, evaluate, and deploy machine learning and data science models for production use.
• Develop and integrate Generative AI solutions using AWS Bedrock, including foundation model selection, prompt engineering, and inference orchestration.
• Design and manage AWS cloud infrastructure using Terraform following IaC best practices.
• Build scalable AI/ML and GenAI deployment architectures using AWS services.
• Develop and optimize data ingestion, processing, and analytics pipelines for structured and unstructured data.
• Collaborate with cross-functional teams to translate business and analytical requirements into technical solutions.
• Implement CI/CD pipelines, monitoring, logging, and performance optimization.
• Ensure security, compliance, governance, and cost optimization of cloud and AI workloads.
• Mentor junior engineers, conduct code reviews, and contribute to architectural decisions.
• Create and maintain technical documentation, solution designs, and operational runbooks.

Requirements

• Minimum 8+ years of overall software engineering experience.
• Engineering Degree (BE/ME/BTech/MTech/BSc/MSc).
• Technical certification in multiple technologies is desirable.

Skills

Mandatory Skills

• Strong proficiency in Python for backend systems, data processing, and ML workflows.
• Hands-on experience in Data Science and Machine Learning, including feature engineering, model evaluation, and deployment.
• Experience with ML frameworks such as Scikit-learn, PyTorch, TensorFlow, or similar.
• Strong experience with AWS services, including EC2, S3, Lambda, ECS/EKS, RDS, SageMaker, and AWS Bedrock.
• Practical knowledge of AWS Bedrock for building and operationalizing Generative AI applications.
• Hands-on experience with Terraform for infrastructure provisioning and environment management.
• Experience building cloud-native, scalable, and highly available systems.
• Solid understanding of data stores (SQL, NoSQL) and data processing architectures.
• Familiarity with Docker, Kubernetes, and modern DevOps practices.
• Strong problem-solving, communication, and collaboration skills.

Good-to-Have Skills

• Prior experience with clinical, biomedical, or healthcare NLP use cases.
• Familiarity with healthcare data standards, terminologies, or ontologies.
• Experience deploying ML/NLP solutions in regulated or production healthcare environments.
• Knowledge of distributed systems and cloud-native data architectures.
• Experience with additional data stores, data warehouses, or NoSQL technologies.
• Strong technical documentation and stakeholder communication skills.
• Experience working in agile or cross-functional product development teams.

Location: Chicago, IL