Top Artificial Intelligence Jobs in Pune

The role requires strong project management and data analysis skills with a focus on technology and AI in the banking sector.

The role involves designing, developing, and deploying AI/ML solutions, managing data pipelines, and optimizing AI systems for operational improvements.

The AI/ML Engineer will design, build, and deploy AI solutions to enhance observability and automation. Responsibilities include developing NLP models, generative AI solutions, and AI-driven analytics while collaborating with cross-functional teams.

Develop and implement digital twin architectures for patient modeling, research AI innovations, mentor junior team members, and contribute to client solutions.

Join the AI Center of Excellence to design AI systems, collaborate with security teams, and optimize machine learning models for threat detection and automation, mentoring junior members in the process.

The role entails leading the delivery of ML solutions, designing pipelines for security use cases, optimizing models on AWS, and mentoring junior engineers.

The role assesses the integrity of the bank's internal controls, influences decision-making, leads teams, and communicates findings to stakeholders. Collaboration and risk mitigation are key responsibilities.

Develop and implement algorithms to solve complex problems, analyze data using statistical techniques, and collaborate with clients to communicate findings.

The AI Engineer will develop and implement AI models, optimize performance, manage data handling, and collaborate with teams to align solutions with business goals.

The role involves contributing to agentic AI workflows and LLM systems, as well as developing ML pipelines for security data, under senior guidance. It requires hands-on skills in prompt engineering and RAG pipelines and aims to build strong foundations in AI engineering within a cybersecurity context.

The Lead AI Scientist will design and optimize LLM architectures, fine-tune models, develop AI systems, mentor junior members, and collaborate with clients and teams on AI solutions.

Lead and support execution of ADI's global compliance programs: risk‑based monitoring, policy management, testing, investigations, training, ISO 37301 alignment, audits, remediation, and cross‑functional stakeholder coordination.

Support and enhance ADI's global compliance program aligned to enterprise risk and ISO 37301. Monitor regulatory developments, update policies, execute risk‑based monitoring and testing, manage investigations and remediation, support audits, develop training and communications, track metrics, and collaborate with Legal, HR, Finance, IT, and Operations to drive continuous improvement.

As a Staff Backend Engineer, you'll design backend architecture for AI governance, ensuring auditability and compliance, while collaborating with engineering teams to enhance product capabilities.

Evaluate AI-generated technical content, craft and answer advanced ML/AI prompts, assess model responses for accuracy, relevance, and clarity, identify errors or hallucinations, and provide feedback to improve AI systems.

The BIA VP - Finance and Treasury is responsible for auditing, risk management, strategy setting, and stakeholder communication in a banking environment.

Conduct interdisciplinary AI research focused on healthcare, develop and teach related courses, collaborate on complex healthcare data analysis, and secure funding.

Seeking a Product Owner with experience in Java, Python, Springboot, AWS, and Artificial Intelligence to manage product development.

The Lead AI Engineer designs and delivers AI/ML and Generative AI solutions for banking platforms, integrating data and enabling AI-driven decisions.

The Senior Enterprise Systems Engineer will design and maintain scalable cloud infrastructure, automate processes using IaC with Terraform, drive reliability measures, and ensure collaboration across teams for operational efficiency.

Lead an engineering team to build distributed, low-latency Python applications and cloud-native solutions on AWS. Design and operate data ingestion and processing pipelines, manage relational and NoSQL databases, implement CI/CD and DevOps (Docker, Kubernetes, Terraform), and productionize ML/Deep Learning and Generative AI solutions (RAG, LLM fine-tuning, prompt engineering). Ensure governance, security, and observability for scalable, production-grade ML systems.

Design and build end-to-end AI solutions: architect data pipelines, deploy and fine-tune LLMs (RAG/vector DB), implement MLOps (CI/CD, monitoring), create visualizations and ROI-driven model evaluations, educate customers, mentor teammates, and share learnings publicly.

Develop and maintain scalable Python/Django backend systems, integrate and deploy generative AI models (LLMs, embeddings, vector DBs), collaborate with data scientists on model fine-tuning, work with APIs, microservices and databases, optimize performance and security, and research emerging AI/ML tools.

Develop and maintain scalable Python/Django backends integrated with LLMs and AI workflows. Implement APIs, data pipelines, and Agentic AI orchestration. Collaborate with product and ML teams to deploy, optimize, and ensure reliability of AI-driven applications.

Design, build, and deploy GenAI/LLM-powered solutions (chatbots, summarization, document processing, knowledge assistants). Implement prompt engineering, data preprocessing, embeddings, RAG pipelines, and vector DB integrations. Integrate models via REST APIs, collaborate with product and engineering teams, monitor model performance, and ensure responsible AI practices and production-ready deployment.