This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Machine Learning Architect - REMOTE. In this role, you will be pivotal in designing, deploying, and optimizing data-driven machine learning solutions on AWS. Your expertise will drive the creation of secure and scalable ML systems, enabling effective data management and model deployment. You'll engage closely with clients and lead the enhancement of best practices within the data and ML lifecycle, making a substantial impact across projects and teams. Your guidance will not only support client objectives but also foster growth among team members.AccountabilitiesDesigning, implementing, and maintaining end-to-end ML architecture using AWS servicesLeading data acquisition, cleaning, and transformation workflows using AWS Glue and LambdaBuilding scalable data pipelines to feed ML models with high-quality, production-grade dataCollaborating with data engineers and scientists to optimize model input/output processesDeploying and managing models using SageMaker endpoints, pipelines, and the model registrySelecting appropriate AWS storage and database services (S3, RDS, Redshift) to support ML use casesDeveloping automated workflows for model training, evaluation, and retraining using Step Functions and MLOps best practicesAssisting clients in migrating legacy ML solutions to cloud-native platformsTroubleshooting data pipeline and model deployment issuesParticipating in project planning, client meetings, and delivery reviewsContributing to internal R&D projects that evaluate new AWS ML and data servicesMentoring junior team members on data modeling, ML deployment, and data architecture best practicesRemaining up to date with ML, AI, and data technology trendsAdvising clients on responsible AI practices, data governance, and compliance in model developmentRequirements5+ years of professional IT or software engineering experience2+ years of hands-on AWS experience in ML and data workloadsAt least one AWS Certification (preferably Machine Learning – Specialty or Solutions Architect – Professional)Experience with Amazon SageMaker: model training, hosting, custom containers, and PipelinesProficiency with SageMaker Studio for end-to-end ML developmentStrong knowledge of AWS data services including Amazon S3, AWS Glue, and Amazon RDSFamiliarity with streaming data and batch processing using Lambda, Step Functions, or KafkaProficiency in Python and frameworks such as Scikit-Learn, TensorFlow, PyTorch, and PandasExperience with NLP and CV services like Amazon Comprehend and RekognitionStrong SQL skills and familiarity with both relational and NoSQL data storesKnowledge of data modeling, dimensional modeling, and building feature storesExperience designing and implementing MLOps workflows, CI/CD, and monitoring practicesUnderstanding of data privacy, model drift, bias detection, and explainability techniquesBonus: Experience working with big data platforms like Apache Spark, EMR, or Lake FormationBenefitsCompetitive OTE Compensation Range: $175K-$200K dependent on experienceFlexible remote work environment with minimal travel requiredOpportunities for professional growth and developmentAccess to cutting-edge technologies and platformsCollaborative and supportive team cultureEngagement in innovative and impactful projectsMentorship opportunities to develop leadership skillsWhy Apply Through Jobgether? We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the bestData Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.#LI-CL1