Chevron has announced a new opening for a Senior Machine Learning Engineer at its Engineering and Innovation Excellence Center (ENGINE) in Bengaluru, Karnataka, India. The role forms part of Chevron’s global push to strengthen artificial intelligence, machine learning, and digital innovation capabilities across its energy operations.

The ENGINE hub in Bengaluru brings together global expertise and local engineering talent to develop advanced technological solutions aimed at improving 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 Bengaluru-based ENGINE center plays a strategic role in:

Advancing AI and machine learning applications in energy systems
Improving operational efficiency through automation
Supporting global engineering and data science initiatives
Developing scalable digital infrastructure for enterprise use

The Senior Machine Learning Engineer position is central to building intelligent systems that support Chevron’s long-term innovation strategy.

Role Overview: Senior Machine Learning Engineer

The Senior Machine Learning Engineer will be responsible for designing, deploying, and maintaining advanced machine learning systems that operate at scale in production environments.

The role focuses heavily on machine learning operations (MLOps), infrastructure development, and model lifecycle management.

Key areas of responsibility include:

Designing and managing CI/CD pipelines for ML models
Automating model training, validation, and deployment workflows
Building scalable cloud-based ML infrastructure
Optimizing system performance and resource efficiency
Supporting distributed training and real-time inference systems

The position requires close collaboration with data scientists, software engineers, and DevOps teams.

Focus on MLOps, Scalability, and Production Systems

A core part of the role involves building reliable and scalable machine learning systems for enterprise use. The engineer will be expected to ensure that models are not only accurate but also operationally stable in production environments.

Responsibilities in this area include:

Implementing model monitoring systems for drift detection and performance tracking
Ensuring compliance with data governance, privacy, and security standards
Establishing observability frameworks including SLOs and alerting systems
Maintaining reproducibility and version control for machine learning models

These responsibilities reflect Chevron’s increasing focus on responsible and production-grade AI systems.

Technical Stack and Required Expertise

Candidates for the role are expected to bring strong technical expertise in software engineering and machine learning infrastructure.

Required skills include:

Advanced proficiency in Python
Experience with Docker and Kubernetes
Cloud computing expertise (AWS, Azure, or GCP)
Knowledge of ML lifecycle platforms such as MLflow, TFX, or Airflow
Strong understanding of model deployment and versioning strategies

The role requires 8–10 years of professional experience in software engineering, data science, or MLOps.

Preferred Skills and Advanced Capabilities

Chevron has also outlined preferred qualifications for candidates with deeper specialization in machine learning systems and advanced AI applications.

Preferred skills include:

Experience in computer vision or domain-specific ML applications
Knowledge of feature stores such as Feast or Tecton
Familiarity with monitoring tools like Evidently AI, Arize AI, or Roboflow
Experience with distributed training frameworks such as Ray or Horovod
Expertise in experiment tracking tools like MLflow or Weights & Biases

Candidates with experience in full ML lifecycle production systems, from data ingestion to monitoring, are considered highly competitive.

Leadership and Collaboration Expectations

Beyond technical expertise, the role also requires leadership and collaboration skills within cross-functional engineering teams.

The Senior Machine Learning Engineer will:

Mentor junior engineers and contribute to technical leadership
Collaborate across data science, DevOps, and software engineering teams
Develop reusable ML components and infrastructure libraries
Evaluate emerging AI tools and technologies for enterprise adoption

The position emphasizes both technical depth and strategic influence within Chevron’s engineering ecosystem.

Chevron’s Vision for Innovation and Energy Transformation

Chevron states that its long-term vision is to be the most admired global energy company through innovation, partnerships, and performance. The company emphasizes the development of “affordable, reliable, ever-cleaner energy” as part of its mission to support global progress.

The ENGINE center in Bengaluru reflects this vision by integrating advanced digital tools into energy systems and supporting global operations through engineering excellence.

Work Environment and Employee Benefits

The role is based in a modern engineering environment designed to support innovation, collaboration, and well-being.

Key workplace features include:

Structured learning and mentorship opportunities
Collaborative global engineering teams
Digital tools for remote and hybrid coordination
Focus on safety, innovation, and performance
Opportunities to work on large-scale global energy projects

Chevron also emphasizes employee development through continuous learning and exposure to emerging technologies.

Application and Employment Conditions

Applicants are required to submit their applications through Chevron’s official career platform. The company has stated that visa sponsorship is not available for this position in certain cases.

Additional conditions include:

Standard work schedule aligned with global operations
Monday to Friday workweek
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. The position offers experienced engineers the opportunity to contribute to large-scale machine learning systems, cloud infrastructure, and AI-driven innovation within one of the world’s largest energy companies.

As Chevron continues to expand its digital capabilities, roles like this are expected to play a critical part in shaping the future of intelligent energy systems.

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