Chevron has announced the opening of a new restaurant. Senior Machine Learning Engineer At the Engineering & Innovation Excellence Center (ENGINE), Bengaluru, Karnataka, India. The role forms part of Chevron’s global efforts to strengthen its artificial intelligence, machine learning and digital innovation capabilities across its energy business.
The ENGINE hub in Bangalore brings together global expertise and local engineering talent to develop advanced technology solutions aimed at increasing efficiency, scalability and innovation in the energy sector.
Chevron expands AI and ML capabilities in energy innovation
Chevron, a global leader in integrated energy systems, continues to invest heavily in digital transformation. The company operates across crude oil production, natural gas, refining, petrochemicals and energy technologies.
The Bangalore-based ENGINE Center plays a strategic role in:
- Advances in AI and machine learning applications in energy systems
- Improving operational efficiency through automation
- Supporting global engineering and data science efforts
- Developing scalable digital infrastructure for enterprises
The Senior Machine Learning Engineer position is central to building intelligent systems that support Chevron’s long-term innovation strategy.
Role Summary: Senior Machine Learning Engineer
The Senior Machine Learning Engineer will be responsible for designing, deploying, and maintaining advanced machine learning systems running at scale in production environments.
This role focuses on machine learning operations (MLOps), infrastructure development, and model lifecycle management.
The main areas of responsibility are:
- Design and manage CI/CD pipelines for ML models
- Automate model training, validation, and deployment workflows
- Build a scalable cloud-based ML infrastructure
- Optimize system performance and resource efficiency
- Support for distributed training and real-time inference systems
This position requires close collaboration with data scientists, software engineers, and DevOps teams.
Focus on MLOps, scalability, and production systems
The core of the role involves building reliable and scalable machine learning systems for enterprise use. Engineers are required to ensure that their models are not only accurate, but also operationally stable in production environments.
Responsibilities in this area include:
- Implementing a model monitoring system for drift detection and performance tracking
- Ensure compliance with data governance, privacy, and security standards
- Establishing an observability framework including SLOs and alerting systems
- Maintaining reproducibility and version control for machine learning models
These responsibilities reflect Chevron’s increasing focus on responsible production-grade AI systems.
Technology stack and required expertise
Candidates for this role will be expected to bring strong technical expertise in software engineering and machine learning infrastructure.
The required skills are:
- Advanced Python skills
- Docker and Kubernetes experience
- Cloud computing expertise (AWS, Azure, or GCP)
- Knowledge of ML lifecycle platforms such as MLflow, TFX, and Airflow.
- Deep understanding of model deployment and version control strategies
This role requires 8-10 years of professional experience in software engineering, data science, or MLOps.
Desired skills and advanced abilities
Chevron also outlined recommended qualifications for candidates with deeper expertise in machine learning systems and advanced AI applications.
Preferred skills include:
- Experience with computer vision or domain-specific ML applications.
- Knowledge of feature stores such as Feast and Tecton.
- Knowledge of monitoring tools such as Evidently AI, Arize AI, and Roboflow.
- Experience with distributed training frameworks such as Ray or Horovod.
- Expertise in experiment tracking tools such as MLflow and Weights & Biases
Candidates with experience with operational systems across the ML lifecycle, from data ingestion to monitoring, will be highly competitive.
Expectations for leadership and collaboration
This role requires technical expertise as well as leadership and collaboration skills within a cross-functional engineering team.
The Senior Machine Learning Engineer will:
- Mentor junior engineers and contribute to technical leadership
- Collaboration between data science, DevOps, and software engineering teams
- Develop reusable ML components and infrastructure libraries
- Evaluate new AI tools and technologies for enterprise adoption
This position emphasizes both technical depth and strategic influence within Chevron’s engineering ecosystem.
Chevron’s vision for innovation and energy transformation
Chevron says its long-term vision is to become the most admired global energy company through innovation, partnerships and performance. The company is focused on developing “affordable, reliable, and cleaner energy” as part of its mission to help the world progress.
The ENGINE Center in Bangalore reflects this vision by integrating advanced digital tools into energy systems and supporting global operations through engineering excellence.
Working environment and benefits
This role is based in a modern engineering environment designed to support innovation, collaboration and wellbeing.
The main features of the workplace are:
- Structured learning and teaching opportunities
- Collaborative global engineering team
- Digital tools for remote and hybrid coordination
- Focus on safety, innovation and performance
- Opportunity to work on large-scale global energy projects
Chevron also emphasizes employee development through continuous learning and exposure to new technology.
Application and employment conditions
Applicants must submit applications through Chevron’s official career platform. The company states that in some cases visa sponsorship is not available for this position.
Additional conditions include:
- Standard work schedule for global operations
- Weekly working hours from Monday to Friday
- Flexible working hours based on business requirements
- Compliance with global privacy and employment regulations
conclusion
Chevron’s senior machine learning engineer role in Bengaluru highlights the growing intersection between artificial intelligence and the global energy industry. This position offers an experienced engineer the opportunity to contribute to large-scale machine learning systems, cloud infrastructure, and AI-driven innovation at one of the world’s largest energy companies.
As Chevron continues to expand its digital capabilities, these roles are expected to play a key role in shaping the future of intelligent energy systems.
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Disclaimer: Global South Opportunities (GSO) is not the organization providing this opportunity. For inquiries, please contact the official organization directly. Please do not submit your application or resume to GSO as it cannot be processed by GSO. Due to the large volume of emails we receive every day, we may not be able to reply to all inquiries. Thank you for your understanding.
