AI / ML Engineer
- Accenture
- 8 - 13 years
- Bengaluru
- 6 hours ago
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Job Description
Project Role :AI / ML EngineerProject Role Description :Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills :AI Data Solution ArchitectureGood to Have skills :NA
Minimum 7.5 year(s) of experience is required
Educational Qualification :15 years full time educationSummary lvl 8
FullStack Cognitive Systems Engineer
We''re looking for a visionary FullStack Engineers with at least 8+ years of hands-on experience in building cognitive, AI/ML-driven platforms across on-prem HCIs, private cloud, and public cloud stacks, to work on business-critical client environments. The role requires strong architectural solutioning skills, statistical and analytical depth, and proven experience delivering end-to-end production AI systems, including time-series forecasting, recommendation engines, clustering, NLP, and deep learning solutions. The focus is to manage client technology landscapes, drive cross-technology migrations and modernization, handle technology crisis management, and add measurable business value through innovation while addressing complex technical challenges faced by enterprise clients.Roles Responsibilities:
- Architect and deliver end-to-end AI/ML solutions, covering problem formulation, statistical modeling, feature engineering, model development, evaluation, and production deployment, with ownership across the full lifecycle.
- Apply strong statistical foundations (probability, hypothesis testing, regression, time-series analysis) to design robust, explainable, and reliable ML systems.
- Design and implement knowledge-driven architectures, including knowledge graphs, ,entity relationship modeling, and semantic layers and decision intelligence.
- Build and productionize time-series forecasting systems, recommendation engines, clustering and segmentation models, anomaly detection pipelines, NLP, and deep learning solutions for enterprise use cases.
- Implement and maintain MLOps practices, including CI/CD for ML, model versioning, monitoring, drift detection, retraining strategies, scalable inference, and governance.
- Collaborate with architects and platform teams to perform architectural solutioning, translating business and data problems into scalable, resilient, cloud-native system designs.
- Design, develop, and maintain end-to-end cognitive HCIs, Private cloud integrating intelligence into traditional web stacks.
- Develop and manage full stack infrastructure platforms including backend services (APIs, microservices) and API gateway for frontend and backend services.
- Understand the impact of GPU based computing and have experience in deploying High Performance Computing environments
- AWS Outpost, Azure Stack, Google cloud VPC Certified and implementation knowledge.
- Tanzu, Red Hat Openshift cluster deployment on Private cloud Deisgn, Deploy and Maintain.
- Develop cloud-native back-end services using Node.js, Python (FastAPI, Flask), or Java to connect AI models with application logic.
- Integrate AI/ML models (TensorFlow, PyTorch, scikit-learn) into production-ready APIs and microservices.
- Write efficient, maintainable code and manage integration between front-end interfaces and back-end infrastructure services.
- Collaborate with product, design, ML, and DevOps teams to build intelligent workflows and user experiences
- Implement Infrastructure as Code (IaC) using tools like Terraform, CloudFormation, AZURE DEV OPS or Pulumi or GCP .
- Deploy and manage Platform-as-a-Service (PaaS) offerings.
- Design, implement, and maintain database solutions, including relational databases (e.g., MySQL, PostgreSQL, SQL Server) and NoSQL databases (e.g., MongoDB, DynamoDB)
- Collaborate with DevOps, security, and development teams to ensure seamless integration and delivery.
- Ensure platform observability via metrics, logging, and monitoring frameworks (e.g., Prometheus, ELK, CloudWatch).
- Manage containerization and orchestration using Docker and Kubernetes.
- Ensure compliance with security best practices and organizational policies.
- Continuously evaluate and implement new cloud technologies and tools to improve efficiency.
- Provide technical guidance and support to team members and stakeholders.
- Integrate and support AI-driven tools and frameworks, including Generative AI and Agentic AI technologies, within cloud infrastructure and applications.
Telecom domain expertise:
-Strong understanding of mobile network technologies, including 2G, 3G, 4G, and 5G architectures, RAN protocols, and radio propagation principles.
-Mandatory expertise in radio network planning and design concepts and methodologies.
-Hands on experience with OSS platforms from major OEMs such as Ericsson, Nokia, and Huawei, with expert level knowledge of RAN/Core OSS KPIs and practical exposure to KPI optimization.
-Experience in customer experience management within telecom networks, including understanding of multiple data sources such as crowd-sourced data, drive test data, probe data, network traces, and strong capability to correlate these datasets for insights.
-Knowledge of emerging telecom technologies, including Open RAN architecture, RIC (Near RT/Non RT), R Apps, xApps, and understanding of their integration and impact on legacy network environments.
-Strong understanding of OEM-specific radio network parameters, counters, and KPIs, along with knowledge of radio features and the latest 3GPP releases.
-Experience with SON (Self Organizing Networks) modules from any Tier 1 OEM, including configuration, operation, and optimization of SON functionalities.Professional and Technical Skills:
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Data Platform EngineerEmployement Type: Full timeContact Details:
Company: AccentureLocation(s): Bengaluru+ View Contact
Keyskills: ml engineer api gateway devops engineer redis sql microservices docker java postgresql shell scripting mysql mongodb ml architecture front end python forecasting ai sql server nosql back end r compliance full stack flask
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