Senior Python/Java Engineer – AI/ML Platforms, VP
Deutsche Bank View all jobs
- Bangalore, Karnataka
- Permanent
- Full-time
- The Senior Engineer designs and implements AI‑driven technical solutions and configures applications across environments to solve complex business problems. With partial/full ownership of AI/ML production platforms, the Senior Engineer ensures environment stability, rapid resolution of production issues, and continuity of critical ML services.
- The role involves building scalable API‑driven systems, integrating ML models into production, and standardizing reusable components to ensure reliability and performance.
- Best in class leave policy
- Gender neutral parental leaves
- 100% reimbursement under childcare assistance benefit (gender neutral)
- Sponsorship for Industry relevant certifications and education
- Employee Assistance Program for you and your family members
- Comprehensive Hospitalization Insurance for you and your dependents
- Accident and Term life Insurance
- Complementary Health screening for 35 yrs. and above
- Architect, design and develop AI‑enabled backend services using Python and/or Java.
- Build scalable microservices that integrate ML models (training, inference, monitoring).
- Own the full development lifecycle—analysis, design, implementation, testing and L3 support.
- Partner closely with Data Science teams to productionize models and optimize performance.
- Participate in strategic evolution of platform architecture, MLOps pipelines and cloud infra.
- Implement feature engineering, data ingestion workflows, and model serving APIs.
- Work with peer teams to deliver successfully on integration points across AI/ML systems.
- Contribute to SL3 production issue investigation and resolution.
- Document requirements, design decisions, APIs and architecture.
- Collaborate with QA teams to automate testing of new and existing AI functionality.
- Mentor junior developers and guide them on best engineering and ML engineering practices.
- Strong hands-on experience in Python and/or Java for backend engineering.
- Experience building AI/ML applications, integrating models, or developing ML pipelines.
- Solid understanding of REST APIs, microservices, distributed systems.
- Experience with ML frameworks: TensorFlow, PyTorch, Scikit‑learn.
- Strong database knowledge: SQL Server, Oracle, PostgreSQL, or NoSQL stores.
- Experience with Linux, Shell scripting, event‑based frameworks, Kafka.
- Hands-on experience with Docker, Kubernetes, OpenShift, GKE, CI/CD tooling (Jenkins, TeamCity).
- Familiarity with MLOps tools such as MLflow, Airflow, Kubeflow (preferred).
- Strong understanding of design patterns, TDD/BDD, and Agile/DevOps practices.
- Cloud experience with GCP, AWS, or Azure.
- Bonus: experience with Spark, Elastic, Kibana, or AI digitization (OCR, ML, AI automation).
- Training and development to help you excel in your career
- Coaching and support from experts in your team
- A culture of continuous learning to aid progression
- A range of flexible benefits that you can tailor to suit your needs