Note: The job is a remote job and is open to candidates in USA. Rocket Software, a leading provider of enterprise modernization software, is expanding its AI strategy in support of its vision of Modernization Without Disruption. The Technical Director for Machine Learning & Algorithms will define and drive how large-scale ML systems and advanced algorithms are applied to mainframe operational data to deliver monitoring, analysis, optimization, risk detection, and modernization insights.
Responsibilities
- Define and lead Rocket’s machine learning and algorithmic strategy across Infra, App and Data modernization business lines
- Extend that strategy across Rocket’s enterprise analytics platforms, including in-database and embedded ML capabilities, to ensure architectural consistency and reuse
- Act as a hands-on technical leader working with product and engineering teams throughout the full feature lifecycle, from problem framing and model selection to validation, delivery, and operationalization
- Architect large-scale ML and data processing systems that operate on high-volume operational data, including z/OS telemetry, SMF/RMF records, logs, workload metrics, and enterprise analytics datasets
- Design and implement advanced algorithms and statistical models for anomaly detection, pattern analysis, forecasting, optimization, classification, and modernization insights
- Guide the use and evolution of in-database ML and analytics capabilities, including regression, classification, clustering, and time-series techniques, ensuring they are applied correctly, efficiently, and at scale
- Establish ML architectures, technical standards, and best practices that span feature engineering, model training, evaluation, explainability, deployment, and lifecycle management
- Ensure ML-driven insights are explainable, inspectable, and aligned with governance and compliance expectations, particularly in regulated and mission-critical environments
- Collaborate closely with domain experts in mainframe operations, performance, security, and data platforms to translate deep system knowledge into scalable, data-driven intelligence
- Lead across reporting boundaries by influence and technical credibility rather than hierarchy, helping teams solve complex problems at all stages of feature development and delivery
- Partner with Product and Architecture leadership to shape long-term strategy for operational analytics, AI-assisted modernization, and analytics platform evolution
- Engage with enterprise customers to understand real-world operational and analytical constraints and validate ML-driven solutions
- Mentor Principal Engineers and senior technical staff, raising the bar for ML rigor, systems thinking, and operational relevance across Rocket
- Contribute internal and external thought leadership on applied ML for mainframe operations, enterprise analytics, and responsible AI
Skills
- 12+ years of experience in software engineering, ML systems, or advanced algorithm development
- Proven experience owning and delivering ML or algorithmic systems into production at scale
- Strong background in large datasets, distributed processing, and end-to-end ML system design
- Solid coding skills in Python and Java, with foundations in optimization, statistics, and applied mathematics
- Experience building ML or analytics solutions tied to system behavior, performance, observability, or operational telemetry
- Demonstrated ability to operate effectively across teams and organizations through technical leadership and influence
- Track record of mentoring senior technical talent and working as a player-coach
- Strong experience with mainframe systems and data sources such as z/OS, SMF, RMF, Db2, RACF, or mainframe performance analytics
- Experience with analytics databases or in-database ML systems, including model training, evaluation, and execution close to data
- Familiarity with regression, classification, clustering, and time-series techniques used in production analytics systems
- Experience designing explainable, auditable, or compliance-aware ML solutions
- Familiarity with distributed computing frameworks or ML platforms such as Spark, Flink, Ray, or cloud ML pipelines
- PhD in Computer Science, Machine Learning, or a related field
- Publications, patents, or conference contributions in ML, algorithms, systems analytics, or operational monitoring
Benefits
- Unlimited Vacation Time as well as paid holidays and sick time
- Health and Wellness coverage options for Rocketeers and dependents
- Life and disability coverage
- Fidelity 401(k) and Roth Retirement Savings with matching contributions
- Monthly student debt benefit program
- Tuition Reimbursement and Certificate Reimbursement Program opportunities
- Leadership and skills training opportunities
Company Overview
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