We are seeking an AWS Gen AI / ML 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 Compensation, Benefits and Duration

Minimum Compensation: USD 48,000 Maximum Compensation: USD 168,000 Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role. Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees. This position is available for independent contractors No applications will be considered if received more than 120 days after the date of this post