Role Description Translate business goals into measurable ML goals (KPIs, acceptance thresholds) in collaboration with PMs and data scientists. - Own the full lifecycle from prototyping (incl. deep learning and GenAI) to deployment and monitoring. - Develop and maintain observability dashboards and alerts tied to ML metrics and feature drift. - Run and safeguard models in real time. - Pilot new ML tools/frameworks, leading integration into production where appropriate. - Act as a cross-org ML thought leader—aligning product, infra, legal, and UX on responsible ML. Qualifications - Bachelor’s degree in Computer Science, Data Science, IT, or a related field. Master’s preferred or equivalent experience for senior levels. - Level 1: 1–2 years in data science/ML roles; hands-on with frameworks like scikit-learn or PyTorch. - Programming: Python (must), Java/C++ (optional), SQL, Apps Script, ServiceNow. - Frameworks: TensorFlow, PyTorch, scikit-learn, HuggingFace. - Tools: Git, Docker, Kubernetes, Airflow, MLflow, Jupyter, Postman. - Data pipeline skills: SQL, Pandas, data APIs. - Deployment: Flask/FastAPI, CI/CD, REST APIs, cloud functions. - Strong analytical and debugging skills. - Translate business problems into AI solutions. - Communicate effectively with technical and non-technical stakeholders. - Work under Agile or DevOps-based workflows. - Stay current with research and emerging technologies. - Rapidly learn new AI concepts and tools. - Handle ambiguity and balance research with delivery. - Collaborate across globally distributed teams. Requirements - Assist in data cleaning, feature engineering, testing basic ML models, write and debug simple scripts. - Develop ML modules, assist in deployment, support data pipelines, contribute to documentation and unit testing. - Support data preparation, model training under guidance, debug code, attend knowledge sessions. - Develop and maintain smaller AI modules (e.g., anomaly detection), assist in deployments, write technical documentation. - Lead development of scalable ML models, integrate into ITSM systems, ensure compliance and performance metrics. - Architect end-to-end AI platforms, oversee cross-domain projects (e.g., NLP for service desk, CV for asset tracking). Competencies - Technical Expertise: - Understands basic ML/DL principles. - Codes in Python/R. - Familiarity with AI/ML tools such as Jupyter, scikit-learn, or TensorFlow (basic use). - Applies supervised/unsupervised ML methods. - Proficient in TensorFlow/PyTorch. - Uses cloud ML services. - Familiar with ML pipelines. - Documents technical solutions and contributes to code reviews. - Designs and builds production-grade models. - Uses MLflow, Airflow, CI/CD tools. - Experience with model deployment and monitoring. - Owns end-to-end AI/ML solutions including architecture, training, deployment, and monitoring. - Applies domain knowledge to improve model relevance (e.g., IT ops, cybersecurity). - Drives model optimization at scale. - Understands data engineering best practices. - Defines org-wide AI/ML standards. - Oversees architecture for reusable platforms. - Directs ML model governance and compliance. - Evaluates and mitigates risks related to fairness, privacy, and regulatory requirements. - Problem Solving & Innovation: - Solves small coding and data cleaning problems. - Ability to analyze and clean datasets. - Identifies root causes in data/model issues. - Applies ML solutions to scoped problems. - Effective in debugging and troubleshooting code and data issues. - Selects and tunes algorithms for real-world impact. - Innovates within team on novel use cases. - Collaboration & Communication: - Good communication and team collaboration skills. - Shares ideas in meetings. - Communicates findings clearly to peers. - Contributes to documentation and demos. - Collaborates cross-functionally to integrate models into services. - Explains model behavior to technical and semi-technical audiences. - Interprets results and presents actionable insights to stakeholders. - Builds trust with cross-functional teams and leadership.