Senior Applied Artificial Intelligence and Machine Learning Engineer

Google India Pvt Ltd; Bengaluru; Presencial; INR 4.000.000 - 7.000.000; Jornada completa

Descripción de la vacante

Google India Pvt Ltd. is seeking a Senior Applied AI/ML Engineer to lead the end-to-end design, development and deployment of AI/ML and agentic solutions within Finance Data and AI (DnA).

You will build models and multi-agent systems that transform legacy finance processes into AI-native workflows, partnering with Googlers across functions. You will drive the technical strategy, ensure reliability, and translate complex probabilistic models for senior executives, while maintaining governance and

Formación

• Master's degree in a quantitative discipline with 4 years of analytics experience.
• 8+ years of experience in full-stack development for end-to-end ML solutions.
• Experience building agentic tools and autonomous agents with governance, logging and human-in-the-loop flows.
• Experience with modern ML/LLM tooling and model deployment to production.
• Strong ability to translate complex architectures into executive-level narratives and collaborate with finance stakeholders.

Responsabilidades

• Lead the technical design of multi-agent workflows using ML tools and Gemini LLMs.
• Build, prototype, and scale end-to-end AI agents.
• Outline architectures prioritizing reliability, usability, and auditability with clear human-in-the-loop interfaces for finance professionals.
• Move prototypes from testing to scaled production systems.
• Design high-availability model endpoints with health checks and retries.
• Implement evaluation frameworks to guard against errors, hallucinations, and biases.
• Partner with Product Managers, Engineers, and Finance to translate problems into specs.
• Provide technical leadership to unblock system integration hurdles with Engineering teams.

Conocimientos

Full-stack development

End-to-end ML

Agentic tools

Autonomous agents

Governance & logging

Human-in-the-loop

Time-series forecasting

Tree-based models

LLM tooling

Model deployment

Observability

Communication skills

Educación

Master's degree in Statistics/Engineering/Sciences

Herramientas

Gemini LLMs

ML Toolkits

Descripción del empleo

Senior Applied AI/ML Engineer

Minimum qualifications: Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience. 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.

Preferred qualifications: 8 years of experience in full-stack development for end-to-end machine learning solutions. Experience building Agentic tools and systems (production-ready, not POCs). Experience building autonomous or semi-autonomous agents with governance, logging, and human-in-loop flows. Experience in classical ML modeling (e.g., time-series forecasting, tree-based models) alongside modern Large Language Model (LLM)/Generative AI tooling. Demonstrated expertise in developing and deploying AI or ML models and utilizing modern observability/monitoring tools to track performance, latency, and model drift. Excellent communication and storytelling skills, with an ability to translate complex technical architectures and probabilistic model behaviors to executive finance leadership.

About the job

Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations. As an Applied AI/ML Engineer, in Finance Data and AI (DnA) team, you will lead the technical strategy, design, and deployment of end-to-end AI/ML and agentic solutions to transform legacy finance processes into AI-native workflows. You will operate at the intersection of advanced machine learning and product-driven transformation. You will build models, design self-sustaining, self-correcting agentic systems that partner with finance Googlers to drive unprecedented efficiency across Google's finance organization.

Responsibilities

• Lead the technical design of multi-agent workflows, utilizing a various toolkit (ML and Gemini LLMs) to solve complex, multi-layered financial problems.


• Build, prototype, and scale end-to-end AI agents.


• Outline system architectures that prioritize reliability, usability, and auditability ensuring clear human-in-the-loop interfaces for finance professionals.


• Take prototypes from isolated testing environments to scaled production systems.


• Design and deploy high-availability model endpoints with health checks, error handling, retries, and fallback mechanisms.


• Implement evaluation frameworks and guardrails to eliminate logical errors, hallucinations, and biases in automated financial decision-making.


• Partner closely with Product Managers, Engineers, and Finance stakeholders to translate ambiguous finance problems into concrete technical specification.


• Act as a self-sustaining technical leadership who helps unblock system integration hurdles in partnership with Engineering teams.

Experience Level

Senior Level