Senior Machine Learning Engineer (Cloud & Data Platform)Role OverviewWe are seeking a highly capable Senior Machine Learning Engineer to support the modernization of enterprise analytics and modeling platforms. This role focuses on migrating and transforming legacy data and machine learning workflows into scalable, cloud-native architectures while improving performance, reliability, and engineering standards.The ideal candidate combines strong ML engineering expertise with deep experience in distributed data processing and cloud data platforms.Key ResponsibilitiesMachine Learning EngineeringDesign, develop, and deploy scalable machine learning models using modern frameworks (e.g., PyTorch)Re-engineer and optimize legacy models into efficient, production-grade implementationsImprove model performance, scalability, and reproducibilitySupport model validation, benchmarking, and certification processesEnsure full traceability and documentation of model logic and outputsData Platform & Pipeline EngineeringDesign and optimize distributed data pipelines using Spark-based platforms (e.g., Databricks)Build and refactor ETL/ELT workflows for performance and scalabilityImplement data models within modern cloud data warehouses (e.g., Snowflake)Apply best practices for cloud-native data architectureStandardize reusable utilities and frameworks for analytics workflowsCloud Migration & ModernizationParticipate in migration of on-prem or legacy analytics platforms to cloud ecosystemsRefactor existing codebases to align with modern engineering and DevOps standardsLeverage cloud compute capabilities (including GPU acceleration where applicable)Support scheduling and orchestration of data and ML workflowsTesting, Validation & GovernanceConduct rigorous testing and validation to ensure data and model accuracyPerform parallel runs and benchmarking when modernizing systemsCollaborate with governance, risk, and compliance stakeholdersMaintain high standards of documentation and reproducibilityRequired QualificationsTechnical SkillsStrong programming skills in PythonHands-on experience with PyTorch (or similar deep learning frameworks)Expertise in Spark-based data processing (Databricks preferred)Strong SQL skillsExperience working with cloud data warehouses such as SnowflakeExperience building and optimizing ETL/ELT pipelinesFamiliarity with distributed computing and performance tuningCloud & DevOpsExperience working in cloud environments (AWS, Azure, or GCP)Understanding of workflow orchestration tools (e.g., Airflow, native platform schedulers)Version control and CI/CD practices for ML pipelinesExposure to containerization and scalable deployment patternsPreferred QualificationsExperience modernizing legacy codebases (C++, R, or similar)Experience in regulated industries (Financial Services, Banking, Insurance, etc.)GPU optimization experienceKnowledge of model risk management or model validation frameworksExperience supporting large-scale data transformation initiatives