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Automotive Machine Learning Jobs (NOW HIRING)

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site

... Automotive. Note: We are currently recruiting for multiple positions, however please only apply for ... Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who ...

Syntiant

Machine Learning Audio Intern

Redwood City, CA · On-site

... automobiles. Syntiant's advanced chip solutions merge deep learning with semiconductor design to produce ultra-low-power, high performance, deep neural network processors. Syntiant also provides ...

PROPRIUS

Senior Machine Learning Engineer

New York, NY

$114K - $157K/yr

... automotive, retail, human resources, training and coaching, media and advertising, video ... Machine Learning Engineer to expand their capacity to next generation vehicles which can act on ...

Syntiant

Machine Learning Audio Intern

Redwood City, CA · On-site

... automobiles. Syntiant's advanced chip solutions merge deep learning with semiconductor design to produce ultra-low-power, high performance, deep neural network processors. Syntiant also provides ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and ...

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How much do automotive machine learning jobs pay per hour?

As of Jun 6, 2026, the average hourly pay for automotive machine learning in the United States is $19.57, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $22.12 per hour, depending on experience, location, and employer.

How does an Automotive Machine Learning specialist typically collaborate with cross-functional teams in the automotive industry?

In the automotive industry, a Machine Learning specialist often works closely with software engineers, data scientists, mechanical engineers, and product managers. This collaboration ensures that machine learning models are effectively integrated into vehicle systems, such as advanced driver-assistance systems (ADAS) or autonomous driving features. Specialists may participate in regular meetings, contribute to code reviews, and help interpret data-driven insights for non-technical stakeholders. Effective communication and teamwork are essential for successfully deploying models that meet both technical and regulatory requirements.

What are the key skills and qualifications needed to thrive in Automotive Machine Learning, and why are they important?

To thrive in Automotive Machine Learning, you need a strong background in computer science, mathematics, and machine learning principles, often supported by a relevant degree and experience in automotive systems. Familiarity with programming languages like Python, machine learning frameworks such as TensorFlow or PyTorch, and automotive-specific tools or simulation environments is typically required. Strong problem-solving abilities, teamwork, and effective communication help professionals collaborate across multidisciplinary teams and translate complex data into actionable insights. These skills are crucial for developing reliable, safe, and innovative machine learning solutions in the rapidly evolving automotive industry.

What is automotive machine learning?

Automotive machine learning refers to the use of artificial intelligence (AI) and machine learning algorithms in the automotive industry. These technologies are applied to improve vehicle safety, enable autonomous driving, optimize manufacturing processes, and enhance user experiences. Machine learning models can analyze data from sensors, cameras, and other vehicle systems to make real-time decisions, such as detecting obstacles, recognizing traffic signs, and predicting maintenance needs. As the automotive industry advances, machine learning is becoming essential for developing smart, connected, and self-driving vehicles.

What is the difference between Automotive Machine Learning vs Automotive Data Analyst?

AspectAutomotive Machine LearningAutomotive Data Analyst
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of ML algorithmsDegree in Data Analytics, Statistics, or related fields; proficiency in data analysis tools
Work EnvironmentDeveloping ML models for vehicle systems, working with engineers and data scientistsAnalyzing vehicle data, generating reports, supporting decision-making
Employer & Industry UsageAutomotive manufacturers, tech companies focusing on autonomous vehiclesAutomotive OEMs, suppliers, dealerships, and service centers

Automotive Machine Learning specialists focus on developing algorithms to improve vehicle systems, while Automotive Data Analysts interpret data to support business decisions. Both roles require strong analytical skills but differ in technical depth and application focus.

Infographic showing various Automotive Machine Learning job openings in the United States as of May 2026, with employment types broken down into 5% As Needed, 79% Full Time, 11% Part Time, and 5% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $40,714 per year, or $19.6 per hour.
Machine Learning Engineering

Machine Learning Engineering

Saanvi Technologies

Dearborn, MI • On-site

Contractor

Posted 22 days ago

Job description

Machine Learning Engineer
 
What You’ll Do:
Collaborate with stakeholders to understand ML requirements and develop innovative solutions. 
Build and maintain scalable ML pipelines, infrastructure, and deployment platforms.
Automate model lifecycle processes with CI/CD/CT and MLOps principles.
Work on analytics pipelines supporting predictive modeling, data flows, and APIs.
Ensure data quality, integrity, and compliance across systems.
Skills & Experience:
3+ years developing ML models in production; strong Python programming.
2+ years hands-on with GCP, BigQuery, Cloud Storage, Cloud Run, and Kubernetes.
Experience with CI/CD tools like Tekton, version control (GitHub), and code quality/security tools.
Familiarity with Spark, Airflow, containerization, and cloud platforms (GCP, AWS, Azure).
Bachelor’s degree in Computer Science or related field (Master’s preferred).
Preferred Skills:
Automotive or analytics experience, ML libraries (TensorFlow, PyTorch, Scikit-learn), MLOps platforms.
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About Saanvi Technologies

Sourced by ZipRecruiter

Saanvi Technologies is a staffing company that specializes in providing IT professionals to businesses. Our employees are experts in their field, and have the skills and experience necessary to help businesses grow and succeed. Saanvi Technologies is dedicated to helping businesses achieve their goals, and they have a proven track record of success. Our employees are qualified and reliable, and they always go above and beyond to meet the needs of their customers.

Company size

51 - 200 Employees

Headquarters location

Farmington, MI, US

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