Data Science/MLOps Engineer

Please find the open requirement below. If you are interested, please share your updated resume, including your expected rate and visa status.

Role: Data Science/MLOps Engineer

Location: Remote, US

Experience: 10+ Years

Contract role

JD-

Summary:

·        Need someone with strong Python and AWS experience. Please check whether we have any previously selected candidates with this tech stack. If not, please look for new candidates who match these requirements.

·        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.

Mandatory skills

·        Strong 6–10 years of overall software engineering experience.

·        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