Data Scientist AWS & Google Cloud Platform | Auto Industry | Local to Atlanta Position Available In Fulton, Georgia

Data Scientist AWS & Google Cloud Platform | Auto Industry | Local to Atlanta
Data Scientist AWS & Google Cloud Platform | Auto Industry

Job Location:

Atlanta, GA

Duration:

Long Term

Job Type:

W2 / Full time

Interview Mode:

2 Rounds (Tech Screening)
Local to Atlanta

Job Description:

We are seeking a Data Scientist with multi-cloud expertise (AWS & Google Cloud Platform) to build and optimize AI/ML solutions for the Auto and Auto Parts Manufacturing industry. This role requires hands-on experience in full ML lifecycle management and the ability to design scalable, industrial-grade ML pipelines using services across both AWS and Google Cloud Platform.

Key Responsibilities:

Develop and deploy ML models for predictive maintenance, quality defect detection, process optimization, and parts lifecycle prediction.
Utilize AWS SageMaker, Google Cloud Platform Vertex AI, and other cloud-native ML services for training and deployment.
Integrate ML models with edge devices and automotive systems (e.g., MES, ERP) and manage real-time data ingestion using AWS Kinesis and Google Cloud Platform Pub/Sub.
Prepare and clean IoT, sensor, and operations data using AWS Glue, Google Cloud Platform Dataflow, or BigQuery.
Implement Generative AI use cases such as smart manuals, production note summarization, and knowledge retrieval using LLMs.
Build robust CI/CD pipelines for ML (MLOps) using Vertex AI Pipelines, SageMaker Pipelines, and GitOps principles.
Collaborate with plant engineers and data teams to align ML outputs with shop floor goals and business KPIs.

Required Skills:

4 7 years of experience with Machine Learning engineering in production environments.
Expertise with AWS ML Stack (SageMaker, Glue, Lambda, S3) and Google Cloud Platform Stack (Vertex AI, BigQuery, Dataflow).
Strong background in Python, data wrangling (Pandas, NumPy), and model development using TensorFlow or PyTorch.
Understanding of automotive manufacturing data (shop floor, sensors, ERP) and related ML use cases.
Hands-on experience with Generative AI tools and LLMs for industrial documentation or analytics.
Proven skills in model monitoring, versioning, and lifecycle management in multi-cloud environments.

Preferred Experience:

Experience with Auto OEMs or Tier-1/2 Auto Parts suppliers.
Familiarity with industrial edge computing, digital twins, or AR/VR based defect tracking.
AWS/Google Cloud Platform certifications related to ML or data engineering are a plus.

Note:

This opportunity is with ITTStar. If interested or if you know someone who is a good fit, please apply or refer.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
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Dice Id:

10501611

Position Id:

8677132