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Deutsche Bank
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AI Lead, VP

AI Lead, VP

Deutsche Bank

10 - 16 years

40 - 45 Lacs

Pune

Posted:22 hours ago| Platform:

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Skills Required

natural language processing time series deep learning data science ml continuous integration python scala ci/cd microsoft azure sql ab testing tensorflow system integration java spark gcp pytorch statistical modeling software engineering api aws

Work Mode

Work from Office

Job Type

Full Time

Job Description

:
Job Title:
AI Lead ,
VP
LocationPune, India
Role Description
Engineer is responsible for managing or performing work across multiple areas of the bank's overall IT Platform/Infrastructure including analysis, development, and administration. It may also involve taking functional oversight of engineering delivery for specific departments.Work includes:

Planning and developing entire engineering solutions to accomplish business goals

Building reliability and resiliency into solutions with appropriate testing and reviewing throughout the delivery lifecycle

Ensuring maintainability and reusability of engineering solutions

Ensuring solutions are well architected and can be integrated successfully into the end-to-end business process flow

Reviewing engineering plans and quality to drive re-use and improve engineering capability

Participating in industry forums to drive adoption of innovative technologies, tools and solutions in the Bank.

Deutsche Banks Corporate Bank division is a leading provider of cash management, trade finance and securities finance. We complete green-field projects that deliver the best Corporate Bank - Securities Services products in the world. Our team is diverse, international, and driven by shared focus on clean code and valued delivery. At every level, agile minds are rewarded with competitive pay, support, and opportunities to excel. You will work as part of a cross-functional agile delivery team. You will bring an innovative approach to software development, focusing on using the latest technologies and practices, as part of a relentless focus on business value. You will be someone who sees engineering as team activity, with a predisposition to open code, open discussion and creating a supportive, collaborative environment. You will be ready to contribute to all stages of software delivery, from initial analysis right through to production support. What well offer you

100% reimbursement under childcare assistance benefit (gender neutral)

Sponsorship for Industry relevant certifications and education

Accident and Term life Insurance

Your key responsibilities

Proven ability to
design, build, and deploy end-to-end AI/ML systems in production.

Expertise in data science, including statistical analysis, experimentation, and data storytelling.

Experienced in working with
large-scale, real-world datasets for model training and analysis.

Comfortable
navigating urgency, ambiguity, and fast-changing priorities. Skilled at solving
complex ML problems independently, from idea to implementation.

Strong leadership experience building and guiding
high-performing AI teams. Hands-on with
deep learning, NLP, LLMs, and classical ML techniques. Fluent in
model experimentation, tuning, optimisation, and evaluation at scale.

Solid software engineering background and comfort working with
data and full-stack teams.

Experience with
cloud platforms (GCP, AWS, Azure) and production-grade ML pipelines.

Bias for action
willing to jump into code, data, or ops to ship impactful AI products.

Your skills and experience

PhD in Computer Science, Data Science, Machine Learning, AI, or a related field.

Strong programming skills in
Python (preferred), with experience in Java, Scala, or Go a plus.

Deep expertise with
ML frameworks like TensorFlow, PyTorch, Scikit-learn.

Experience with
large-scale datasets, distributed data processing (e.g. Spark, Beam, Airflow).

Solid foundation in
data sciencestatistical modeling, A/B testing, time series, and experimentation.

Proficient in
NLP, deep learning, and working with
transformer-based LLMs.

Experience with
MLOps practices CI/CD, model serving, monitoring, and lifecycle management.

Hands-on with
cloud platforms (GCP, AWS, Azure) and tools like Vertex AI, SageMaker, or Databricks.

Strong grasp of
API design, system integration, and delivering AI features in full-stack products.

Comfortable working with
SQL/NoSQL, and data warehouses like BigQuery or Snowflake.

Familiar with
ethical AI, model explainability, and secure, privacy-aware AI development

How well support you

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Deutsche Bank

Banking and Financial Services

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