Collaborates with science, engineering, and product teams to identify business and product needs, and contributes to the identification of solutions to address product and/or business problems. Contributes to end-to-end applied research: surveying state of the art, preparing high-quality datasets, running POCs/experiments, and designing, training, and optimizing ML/AI models and solution architectures. Performs tasks to deliver and deploy solutions into production. Participates in the research community by publishing and presenting research findings.

Key Responsibilities
Solution Identification:
–Collaborates with science, engineering, and product teams to identify business and product needs for machine learning (ML) and/or artificial intelligence (AI) solutions.
–Contributes to literature reviews and state-of-the-art analyses to understand the problem that needs to be solved.
–Contributes to the identification of solutions based on the scientific process (e.g., including modeling approaches, evaluation techniques, data collections).
Solution Development – Applied Research:
–Contributes to the development and piloting of research proofs-of-concept (POCs) or research experiments.
–Identifies datasets to be included in applied research. Reviews and prepares data to ensure high quality data is leveraged with minimal guidance.
–Contributes to research on new theories, tools, and methodologies to transfer and apply state-of-the-art technologies into products and services.
Solution Development:
–Develops ML and AI technologies, such as model training/fine-tuning and computation optimizations.
–Contributes meaningfully to the design of the architecture of ML and AI solutions, such as data, model, training, and evaluation, employing best practices.
Solution Development – Articulating Research Insights:
–Under guidance,



identifies meaningful insights from data and metadata sources from analysis and experiments.
–Interprets and communicates insights and findings to team.
–Participates in the creation of patents, white papers, or other technical documentation related to applied research outcomes.
Solution Delivery – Coding and Documentation:
–Contributes to the development of efficient, bug-free, low-complexity code from scratch and properly maintains and organizes the existing codebase.
–Adheres to best practices for version control, code review, and continuous integration in machine learning projects.
–Updates and maintains qualified documentation for technical processes (experimentation, data collection and analyses, model building).
Solution Delivery:
–Performs delegated tasks with limited guidance to contribute to the delivery of ML/AI solutions and integration of services.
–Participates in collaboration with software engineers and/or machine learning engineers to deploy solutions into production environments.
–Participates in the peer review of solutions prior to delivery.
–Collaborates with operational teams to evaluate and monitor solutions in production.
Building Research Capability – Research Excellence:
–Develops comprehensive knowledge in at least one business-critical applied research technology area.
–Follows guidance to apply domain knowledge and industry best practices to applied research.
Building Research Capability – Research Community Presence:




–Leads the publication and presentation of research findings and papers in conferences, research and industry outlets, etc.
–Participates in the scientific community by providing peer review and feedback.

Core Responsibilities
Planning & Execution:
–Independently manages work, monitoring timelines and deliverables to ensure projects or initiatives stay on track and meet requirements.
–Proactively prioritizes work and adapts to resource or timeline shifts, suggesting adjustments to maintain project efficiency.
Collaboration & Partnership:
–Collaborates across teams to align on expectations and achieve shared objectives.
–Builds and maintains a comprehensive understanding of business, stakeholder, and/or customer needs to build and support effective partnerships.
–Actively listens to diverse perspectives and asks questions to ensure understanding of others.
Problem Solving:
–Independently identifies and addresses standard and non-standard issues in accordance with standard practices, escalating more complex issues as appropriate.
–Analyzes data and/or information from multiple sources to troubleshoot standard and non-standard errors.
–Contributes to knowledge sharing and best practices.
Continuous Learning:
–Embraces continuous learning by actively seeking to build knowledge and new skills and/or tools and staying current with industry trends and best practices.
–Seeks out and leverages feedback and training to improve skills.
–Contributes to a culture of continuous learning and knowledge sharing with team members.
Continuous Improvement:
–Develops ideas and recommends updates to increase the efficiency and effectiveness of processes, protocols, and workflows within a team.
–Seeks input from team members on alternative approaches and methods for improving work.

📌 Senior Applied Scientist (Bengaluru)
🏢 Oracle
📍 Bengaluru