ML- Engineer with AWS

ML-Engineer with AWS Location : Dallas, TX- Onsite Job Description: We are seeking an AWS ML Cloud Engineer to design, deploy, and optimize cloud-native machine-learning systems that power our next-generation predictive-automation platform. You will blend deep ML expertise with hands-on AWS engineering, turning data into low-latency, high-impact insights. The ideal candidate commands statistics, coding, and DevOps—and thrives on shipping secure, cost-efficient solutions at scale. Objectives of this role • Design and productionize cloud ML pipelines (SageMaker, Step Functions, EKS) that advance predictive-automation roadmap • Integrate foundation models via Bedrock and Anthropic LLM APIs to unlock generative-AI capabilities • Optimize and extend existing ML libraries / frameworks for multi-region, multi-tenant workloads • Partner cross-functionally with data scientists, data engineers, architects, and security teams to deliver end-to-end value • Detect and mitigate data-distribution drift to preserve model accuracy in real-world traffic • Stay current on AWS, MLOps, and generative-AI innovations; drive continuous improvement Responsibilities • Transform data-science prototypes into secure, highly available AWS services; choose and tune the appropriate algorithms, container images, and instance types • Run automated ML tests/experiments; document metrics, cost, and latency outcomes • Train, retrain, and monitor models with SageMaker Pipelines, Model Registry, and CloudWatch alarms • Build and maintain optimized data pipelines (Glue, Kinesis, Athena, Iceberg) feeding online/offline inference • Collaborate with product managers to refine ML objectives and success criteria; present results to executive stakeholders • Extend or contribute to internal ML libraries, SDKs, and infrastructure-as-code modules (CDK / Terraform) Skills and qualifications, Primary technical skills • AWS SDK, SageMaker, Lambda, Step Functions • Machine-learning theory and practice (supervised / deep learning) • DevOps & CI/CD (Docker, GitHub Actions, Terraform/CDK) • Cloud security (IAM, KMS, VPC, GuardDuty) • Networking fundamentals • Java, Springboot, JavaScript/TypeScript & API design (REST, GraphQL) • Linux administration and scripting • Bedrock & Anthropic LLM integration • Secondary / tool skills • Advanced debugging and profiling • Hybrid-cloud management strategies • Large-scale data migration • Impeccable analytical and problem-solving ability; strong grasp of probability, statistics, and algorithms • Familiarity with modern ML frameworks (PyTorch, TensorFlow, Keras) • Solid understanding of data structures, modeling, and software architecture • Excellent time-management, organizational, and documentation skills • Growth mindset and passion for continuous learning Preferred qualifications • 10+ years of Software Experience • 3+ years in an ML-engineering or cloud-ML role (AWS focus) • Proficient in Python (core), with working knowledge of Java or R • Outstanding communication and collaboration skills; able to explain complex topics to non-technical peers • Proven record of shipping production ML systems or contributing to OSS ML projects • Bachelor’s (or higher) in Computer Science, Data Engineering, Mathematics, or a related field • AWS Certified Machine Learning – Specialty and/or AWS Solutions Architect – Associate a strong plus Rohan Bhabha rohan@exlneo.com