Machine Learning Engineer (AWS Professional Services)

Job DescriptionRole: Machine Learning Engineer with AWS Professional ServicesExperience: 8+ YearsWork Mode: RemoteLooking for someone who can join us immediatelyAs a Machine Learning Engineer (MLE) in AWS Professional Services, you will work directly with enterprise customers to design, build, and deploy scalable ML and AI solutions on AWS. This is a customer-facing, hands-on technical role that combines deep ML expertise with cloud architecture, consulting, and delivery skills.You will help organizations operationalize AI/ML workloads, modernize data platforms, and accelerate innovation using AWS services.Key ResponsibilitiesPartner with customer stakeholders (data scientists, engineers, architects, executives) to define ML strategy and architecture.Design and implement end-to-end ML pipelines using AWS services such as:Amazon SageMakerAWS LambdaAmazon S3Amazon EMRAmazon BedrockBuild and deploy ML models (supervised, unsupervised, deep learning, NLP, LLMs).Develop MLOps frameworks (CI/CD for ML, model monitoring, feature stores).Lead workshops, architecture reviews, and proof-of-concept engagements.Provide best practices for security, cost optimization, scalability, and reliability.Contribute reusable assets, accelerators, and reference architectures.Mentor customer teams and internal AWS engineers.Basic QualificationsBachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field.6+ years of experience in:Machine learning engineering or data sciencePython and ML libraries (TensorFlow, PyTorch, Scikit-learn)Model deployment and productionizationExperience with cloud platforms (AWS preferred).Strong understanding of:Feature engineeringModel evaluation & experimentationDistributed trainingMLOps conceptsAbility to travel to customer sites (varies by region).Preferred QualificationsExperience delivering ML projects in consulting or customer-facing roles.Hands-on experience with:LLMs, generative AI, RAG architecturesReal-time inference systemsData engineering pipelines (Spark, Kafka)AWS certifications (e.g., AWS Certified Machine Learning – Specialty).Strong communication and stakeholder management skills.Experience in regulated industries (finance, healthcare, public sector).Key CompetenciesCustomer obsessionOwnership mindsetArchitectural thinkingBias for actionAbility to operate in ambiguityStrong documentation and presentation skillsWhat Makes This Role UniqueExposure to diverse industries and cutting-edge AI use casesDirect impact on enterprise AI transformationAccess to AWS internal tooling and ML specialistsOpportunity to influence best practices at global scale

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