Job Title: Sr. Data & ML Engineer (Analytics)
Location: Bangalore
Experience: 712 years
Summary
As a Senior Data & ML Engineer (Analytics) you will play a pivotal role in shaping the future of AI-driven analytics within a global manufacturing environment. You will lead the end-to-end development and deployment of intelligent systems that transform high-velocity IoT and sensor data into strategic insights. This role combines deep technical expertise in predictive modeling time-series analytics and scalable AI infrastructure with a strong focus on operational impact. By architecting robust data pipelines deploying production-grade models and enabling cross-functional teams across the Asia Pacific region you will drive measurable improvements in quality efficiency and innovation. Your work will directly influence business outcomes ensuring AI solutions are not only advanced but also adoptable reliable and aligned with enterprise goals.
Responsibilities
- Design develop and train AI/ML models focused on predictive analytics and anomaly detection for critical business domains including manufacturing sales engineering and marketing.
- Implement advanced time-series forecasting techniques using IoT and sensor data to predict equipment failures maintenance needs and production bottlenecks.
- Build and maintain scalable ETL pipelines and SQL-based data models to support high-throughput real-time data processing.
- Deploy monitor and support AI solutions across internal business units and external partners ensuring seamless integration and adoption.
- Perform hands-on development and optimization using Python (Pandas NumPy Scikit-learn) to deliver production-ready scalable AI applications.
- Architect and manage high-performance compute environments and automated workflows to enable efficient scaling of AI workloads across regions.
Requirements
Requirements:
- 5 years of hands-on experience in AI/ML engineering DevOps or platform development with a strong background in automotive or manufacturing industries.
- Demonstrated expertise in predictive modeling time-series forecasting and large-scale AI model deployment.
- Proficient in cloud platforms (AWS Azure) AI/ML frameworks (e.g. TensorFlow PyTorch) and modern DevOps practices (CI/CD containerization orchestration).
- Strong skills in data engineering including ETL pipeline design SQL modeling and handling complex IoT/sensor data streams.
- Experience with agile development tools such as JIRA and Confluence and a track record of delivering projects in fast-paced environments.
Enablement Scope
- Manage provisioning configuration and lifecycle of AI platforms APIs and development environments (e.g. AWS Azure ML Hugging Face).
- Design and maintain resilient compute clusters and data pipelines optimized for high-performance AI execution and data scalability.
- Establish structured evaluation frameworks to assess model accuracy delivery timelines and AI adoption rates across teams.
---
Strategic Impact
- Accelerate AI adoption across the Asia Pacific region through scalable infrastructure reusable components and standardized delivery processes.
- Foster cross-functional innovation by aligning AI capabilities with manufacturing operations and business objectives.
- Deliver measurable improvements in operational efficiency product quality and process optimization through defined KPIs and success metrics.
Preferred Traits
- Proactive mindset with high adaptability to emerging AI technologies and industrial automation advancements.
- Strong architectural thinking with a focus on scalability performance and long-term sustainability.
- Ability to lead influence and collaborate across diverse cross-functional teams in dynamic fast-paced settings.
- Passion for building robust future-ready AI systems with continuous improvement and operational excellence at the core.
Required Skills:
Job Title: Sr. Data & ML Engineer (Analytics) Location: Bangalore Experience: 712 years Summary As a Senior Data & ML Engineer (Analytics) you will play a pivotal role in shaping the future of AI-driven analytics within a global manufacturing environment. You will lead the end-to-end development and deployment of intelligent systems that transform high-velocity IoT and sensor data into strategic insights. This role combines deep technical expertise in predictive modeling time-series analytics and scalable AI infrastructure with a strong focus on operational impact. By architecting robust data pipelines deploying production-grade models and enabling cross-functional teams across the Asia Pacific region you will drive measurable improvements in quality efficiency and innovation. Your work will directly influence business outcomes ensuring AI solutions are not only advanced but also adoptable reliable and aligned with enterprise goals. Responsibilities Design develop and train AI/ML models focused on predictive analytics and anomaly detection for critical business domains including manufacturing sales engineering and marketing. Implement advanced time-series forecasting techniques using IoT and sensor data to predict equipment failures maintenance needs and production bottlenecks. Build and maintain scalable ETL pipelines and SQL-based data models to support high-throughput real-time data processing. Deploy monitor and support AI solutions across internal business units and external partners ensuring seamless integration and adoption. Perform hands-on development and optimization using Python (Pandas NumPy Scikit-learn) to deliver production-ready scalable AI applications. Architect and manage high-performance compute environments and automated workflows to enable efficient scaling of AI workloads across regions. Requirements Requirements: 5 years of hands-on experience in AI/ML engineering DevOps or platform development with a strong background in automotive or manufacturing industries. Demonstrated expertise in predictive modeling time-series forecasting and large-scale AI model deployment. Proficient in cloud platforms (AWS Azure) AI/ML frameworks (e.g. TensorFlow PyTorch) and modern DevOps practices (CI/CD containerization orchestration). Strong skills in data engineering including ETL pipeline design SQL modeling and handling complex IoT/sensor data streams. Experience with agile development tools such as JIRA and Confluence and a track record of delivering projects in fast-paced environments. Enablement Scope Manage provisioning configuration and lifecycle of AI platforms APIs and development environments (e.g. AWS Azure ML Hugging Face). Design and maintain resilient compute clusters and data pipelines optimized for high-performance AI execution and data scalability. Establish structured evaluation frameworks to assess model accuracy delivery timelines and AI adoption rates across teams. --- Strategic Impact Accelerate AI adoption across the Asia Pacific region through scalable infrastructure reusable components and standardized delivery processes. Foster cross-functional innovation by aligning AI capabilities with manufacturing operations and business objectives. Deliver measurable improvements in operational efficiency product quality and process optimization through defined KPIs and success metrics. Preferred Traits Proactive mindset with high adaptability to emerging AI technologies and industrial automation advancements. Strong architectural thinking with a focus on scalability performance and long-term sustainability. Ability to lead influence and collaborate across diverse cross-functional teams in dynamic fast-paced settings. Passion for building robust future-ready AI systems with continuous improvement and operational excellence at the core.
Required Education:
Graduate
Job Title: Sr. Data & ML Engineer (Analytics)Location: BangaloreExperience: 712 yearsSummaryAs a Senior Data & ML Engineer (Analytics) you will play a pivotal role in shaping the future of AI-driven analytics within a global manufacturing environment. You will lead the end-to-end development and dep...
Job Title: Sr. Data & ML Engineer (Analytics)
Location: Bangalore
Experience: 712 years
Summary
As a Senior Data & ML Engineer (Analytics) you will play a pivotal role in shaping the future of AI-driven analytics within a global manufacturing environment. You will lead the end-to-end development and deployment of intelligent systems that transform high-velocity IoT and sensor data into strategic insights. This role combines deep technical expertise in predictive modeling time-series analytics and scalable AI infrastructure with a strong focus on operational impact. By architecting robust data pipelines deploying production-grade models and enabling cross-functional teams across the Asia Pacific region you will drive measurable improvements in quality efficiency and innovation. Your work will directly influence business outcomes ensuring AI solutions are not only advanced but also adoptable reliable and aligned with enterprise goals.
Responsibilities
- Design develop and train AI/ML models focused on predictive analytics and anomaly detection for critical business domains including manufacturing sales engineering and marketing.
- Implement advanced time-series forecasting techniques using IoT and sensor data to predict equipment failures maintenance needs and production bottlenecks.
- Build and maintain scalable ETL pipelines and SQL-based data models to support high-throughput real-time data processing.
- Deploy monitor and support AI solutions across internal business units and external partners ensuring seamless integration and adoption.
- Perform hands-on development and optimization using Python (Pandas NumPy Scikit-learn) to deliver production-ready scalable AI applications.
- Architect and manage high-performance compute environments and automated workflows to enable efficient scaling of AI workloads across regions.
Requirements
Requirements:
- 5 years of hands-on experience in AI/ML engineering DevOps or platform development with a strong background in automotive or manufacturing industries.
- Demonstrated expertise in predictive modeling time-series forecasting and large-scale AI model deployment.
- Proficient in cloud platforms (AWS Azure) AI/ML frameworks (e.g. TensorFlow PyTorch) and modern DevOps practices (CI/CD containerization orchestration).
- Strong skills in data engineering including ETL pipeline design SQL modeling and handling complex IoT/sensor data streams.
- Experience with agile development tools such as JIRA and Confluence and a track record of delivering projects in fast-paced environments.
Enablement Scope
- Manage provisioning configuration and lifecycle of AI platforms APIs and development environments (e.g. AWS Azure ML Hugging Face).
- Design and maintain resilient compute clusters and data pipelines optimized for high-performance AI execution and data scalability.
- Establish structured evaluation frameworks to assess model accuracy delivery timelines and AI adoption rates across teams.
---
Strategic Impact
- Accelerate AI adoption across the Asia Pacific region through scalable infrastructure reusable components and standardized delivery processes.
- Foster cross-functional innovation by aligning AI capabilities with manufacturing operations and business objectives.
- Deliver measurable improvements in operational efficiency product quality and process optimization through defined KPIs and success metrics.
Preferred Traits
- Proactive mindset with high adaptability to emerging AI technologies and industrial automation advancements.
- Strong architectural thinking with a focus on scalability performance and long-term sustainability.
- Ability to lead influence and collaborate across diverse cross-functional teams in dynamic fast-paced settings.
- Passion for building robust future-ready AI systems with continuous improvement and operational excellence at the core.
Required Skills:
Job Title: Sr. Data & ML Engineer (Analytics) Location: Bangalore Experience: 712 years Summary As a Senior Data & ML Engineer (Analytics) you will play a pivotal role in shaping the future of AI-driven analytics within a global manufacturing environment. You will lead the end-to-end development and deployment of intelligent systems that transform high-velocity IoT and sensor data into strategic insights. This role combines deep technical expertise in predictive modeling time-series analytics and scalable AI infrastructure with a strong focus on operational impact. By architecting robust data pipelines deploying production-grade models and enabling cross-functional teams across the Asia Pacific region you will drive measurable improvements in quality efficiency and innovation. Your work will directly influence business outcomes ensuring AI solutions are not only advanced but also adoptable reliable and aligned with enterprise goals. Responsibilities Design develop and train AI/ML models focused on predictive analytics and anomaly detection for critical business domains including manufacturing sales engineering and marketing. Implement advanced time-series forecasting techniques using IoT and sensor data to predict equipment failures maintenance needs and production bottlenecks. Build and maintain scalable ETL pipelines and SQL-based data models to support high-throughput real-time data processing. Deploy monitor and support AI solutions across internal business units and external partners ensuring seamless integration and adoption. Perform hands-on development and optimization using Python (Pandas NumPy Scikit-learn) to deliver production-ready scalable AI applications. Architect and manage high-performance compute environments and automated workflows to enable efficient scaling of AI workloads across regions. Requirements Requirements: 5 years of hands-on experience in AI/ML engineering DevOps or platform development with a strong background in automotive or manufacturing industries. Demonstrated expertise in predictive modeling time-series forecasting and large-scale AI model deployment. Proficient in cloud platforms (AWS Azure) AI/ML frameworks (e.g. TensorFlow PyTorch) and modern DevOps practices (CI/CD containerization orchestration). Strong skills in data engineering including ETL pipeline design SQL modeling and handling complex IoT/sensor data streams. Experience with agile development tools such as JIRA and Confluence and a track record of delivering projects in fast-paced environments. Enablement Scope Manage provisioning configuration and lifecycle of AI platforms APIs and development environments (e.g. AWS Azure ML Hugging Face). Design and maintain resilient compute clusters and data pipelines optimized for high-performance AI execution and data scalability. Establish structured evaluation frameworks to assess model accuracy delivery timelines and AI adoption rates across teams. --- Strategic Impact Accelerate AI adoption across the Asia Pacific region through scalable infrastructure reusable components and standardized delivery processes. Foster cross-functional innovation by aligning AI capabilities with manufacturing operations and business objectives. Deliver measurable improvements in operational efficiency product quality and process optimization through defined KPIs and success metrics. Preferred Traits Proactive mindset with high adaptability to emerging AI technologies and industrial automation advancements. Strong architectural thinking with a focus on scalability performance and long-term sustainability. Ability to lead influence and collaborate across diverse cross-functional teams in dynamic fast-paced settings. Passion for building robust future-ready AI systems with continuous improvement and operational excellence at the core.
Required Education:
Graduate
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