Lead Machine Learning Engineer

Overview

Chevron invites applications for the role of Lead AI/ML Engineer in India. This position is integral to designing and developing AI/ML models that significantly accelerate the delivery of business value. We are looking for a Lead Machine Learning Engineer with the ability to bring their expertise, innovative attitude, and excitement for solving complex problems with modern technologies and approaches. We are looking for those few individuals with a passion for exploring, innovating, and delivering innovative Data Science solutions that provide immense value to our business. This Lead role has an expectation of 10-15 years of relevant experience and will provide mentorship to junior members of the team.

Key Responsibilities

• Transform data science prototypes into appropriate scale solutions in a production environment
• Orchestrate and configure infrastructure that assists Data Scientists and analysts in building low latency, scalable and resilient machine learning, and optimization workloads into an enterprise software product
• Combine expertise in mathematics, statistics, computer science, and domain knowledge to create advanced AI/ML models.
• Collaborate closely with the AI Technical Manager and GCC Petro-technical professionals and data engineers to integrate and scale models into the business framework.
• Identify data, appropriate technology, and architectural design patterns to solve business challenges using Chevron approved standard analytical tools and AI design patterns and architectures
• Partner with Data Scientists and Chevron IT Foundational services to implement complex algorithms and models into enterprise scale machine learning pipelines
• Run machine learning experiments and fine-tune algorithms to ensure optimal performance
• Consistently deliver complex, innovative, and complete solutions, driving them through design, planning, development, and deployment that simplify business processes and workflows to drive business value
• Work collaboratively with a large variety of different teams, including data scientists, data engineers, and solution architects from various organizations within business units and IT
• Provide mentorship for other team members
  
  

• Minimum 5 years’ experience in Object Oriented Design and/or Functional Programming in Python. 10 - 15 years of experience
• Mature software engineering skills, such as source control versioning, requirement spec, architecture, and design review, testing methodologies, CI/CD, etc.
• Must have a disciplined, methodical, minimalist approach to designing and constructing layered software components that can be embedded within larger frameworks or applications.
• Experience implementing machine learning frameworks and libraries such as MLflow
• Experience with containers and container managements (docker, Kubernetes)
• Experience developing cloud first solutions using Microsoft Azure Services including building machine learning pipelines in Azure Machine Learning and/or Fabric, Hands-on experience in deploying machine learning pipelines with Azure Machine Learning SDK
• Working knowledge of mathematics (primarily linear algebra, probability, statistics), and algorithms.
• Proficient at orchestrating large-scale ML/DL jobs, leveraging big data tooling and modern container orchestration infrastructure, to tackle distributed training and massive parallel model executions on cloud infrastructure.
• Experience designing custom APIs for machine learning models for training and inference processes and designing, implementing, and delivering frameworks for MLOps.
• Experience with model lifecycle management and automation to support retraining and model monitoring
• Experience implementing and incorporating ML models on unstructured data using cognitive services and/or computer vision as part of AI solutions and workflows.
• History of working with large scale model optimization and hyperparameter tuning, applied to ML/DL models.
• Knowledge of enterprise SaaS complexities including security/access control, scalability, high availability, concurrency, online diagnoses, deployment, upgrade/migration, internationalization, and production support.
• Knowledge of data engineering and transformation tools and patterns such as Databricks, Spark, Azure Data Factory
• Ability to engage other technical experts at all organizational levels and assess opportunities to apply machine learning and analytics to improve business workflows and deliver information and insight to support business decisions.
• Ability to communicate in a clear, concise, and understandable manner both orally and in writing.
  
  

Chevron ENGINE supports global operations, supporting business requirements across the world. Accordingly, the work hours for employees will be aligned to support business requirements. The standard work week will be Monday to Friday. Working hours are 8:00am to 5:00pm or 1.30pm to 10.30pm.