Senior AI Machine Learning Engineer

Chevron India

2 - 4 years

16 - 20 Lacs

bengaluru

Posted:1 week ago| Platform:

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Skills Required

functional python spark testing methodologies sdk artificial intelligence programming docker

Work Mode

Work from Office

Job Type

Full Time

Job Description

Transform data science prototypes into scalable solutions in a production environment.
Orchestrate and configure infrastructure to assist Data Scientists and analysts in building low latency, scalable, and resilient machine learning and optimization workloads.
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.

Job Requirements

Minimum 5 years of experience in Object-Oriented Design and/or Functional Programming in Python.
Experience implementing machine learning frameworks and libraries such as MLflow.
Experience with containers and container management (Docker, Kubernetes).
Experience developing cloud-first solutions using Microsoft Azure Services, including building machine learning pipelines in Azure Machine Learning and/or Fabric.
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.
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/migrations, 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.

Additional Info

The company offers a dynamic work environment and opportunities for professional growth and development.

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