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Remote Tesla Machine Learning Engineer Jobs in New Jersey

GMV

AI Innovation Leader

North Brunswick, NJ · On-site +1

If you want to know more about Big Data, artificial intelligence or machine learning and how they are changing the world, your place is here! We are an engineering and innovation company working in ...

GMV

Data Architect

North Brunswick, NJ · On-site +1

$67.25 - $86.50/hr

If you want to know more about Big Data, artificial intelligence or machine learning and how they are changing the world, your place is here! We are an engineering and innovation company working in ...

Akkadian Labs

DevOps Engineer

Hoboken, NJ · On-site +1

$57.75 - $79/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Experience supporting AI or machine learning workloads, compute environments. * Exposure to AI ... Benefits We offer a fully remote environment, plus a competitive benefits package including medical ...

Akkadian Labs

DevOps Engineer

Hoboken, NJ · Remote

$57.75 - $79/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Experience supporting AI or machine learning workloads, compute environments. * Exposure to AI ... Benefits We offer a fully remote environment, plus a competitive benefits package including medical ...

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Showing results 41-60

All JobsTesla Machine Learning Engineer JobsRemote Tesla Machine Learning Engineer JobsRemote Tesla Machine Learning Engineer Jobs in New Jersey

Remote Tesla Machine Learning Engineer information

What does a remote Tesla machine learning engineer do?

A Remote Tesla Machine Learning Engineer is responsible for designing, developing, and deploying machine learning models to improve Tesla's products and services. Working from a remote location, they collaborate with teams to analyze large datasets, build predictive models, and optimize algorithms for applications such as autonomous driving, energy management, and manufacturing. They also ensure that machine learning solutions are scalable and meet Tesla's high standards for performance and safety.

What are some common challenges faced by remote Tesla machine learning engineers, and how can they be overcome?

Remote Tesla Machine Learning Engineers often face challenges such as collaborating across different time zones, ensuring effective communication with cross-functional teams, and maintaining access to high-performance computing resources. To overcome these, engineers typically use collaborative tools for code sharing and project management, participate in regular virtual meetings, and leverage Tesla's robust cloud infrastructure for experimentation and model training. Proactively seeking feedback and staying aligned with team goals are also key practices for success in this remote, fast-paced environment.

What are the key skills and qualifications needed to thrive as a remote Tesla machine learning engineer?

To thrive as a Remote Tesla Machine Learning Engineer, you need a strong background in computer science, mathematics, and machine learning principles, typically demonstrated through a relevant degree or equivalent experience. Proficiency with Python, TensorFlow or PyTorch, cloud platforms, and version control systems is crucial, and certifications in AI/ML can be advantageous. Exceptional problem-solving, communication, and self-motivation are important soft skills for collaborating remotely and tackling complex projects. These skills enable engineers to design, implement, and scale innovative AI solutions that drive Tesla's technology forward.

What is the difference between Remote Tesla Machine Learning Engineer vs Remote Data Scientist?

AspectRemote Tesla Machine Learning EngineerRemote Data Scientist
Required CredentialsDegree in Computer Science, Engineering, or related field; experience with ML frameworksDegree in Statistics, Mathematics, or related field; strong programming skills
Work EnvironmentCollaborates with engineering teams on autonomous systems and vehicle dataAnalyzes large datasets to extract insights for business or product decisions
Employer & Industry UsagePrimarily in automotive, tech, and autonomous vehicle sectorsAcross tech, finance, healthcare, and various industries

While both roles involve data analysis and machine learning, the Remote Tesla Machine Learning Engineer focuses on developing algorithms for autonomous vehicles, whereas the Remote Data Scientist analyzes data to inform business strategies. The roles share similar credentials but differ in application and industry focus.

What are the most commonly searched types of Tesla Machine Learning Engineer jobs in New Jersey?

The most popular types of Tesla Machine Learning Engineer jobs in New Jersey are:

What are popular job titles related to Remote Tesla Machine Learning Engineer jobs in New Jersey?

For Remote Tesla Machine Learning Engineer jobs in New Jersey, the most frequently searched job titles are:

What job categories do people searching Remote Tesla Machine Learning Engineer jobs in New Jersey look for?

The top searched job categories for Remote Tesla Machine Learning Engineer jobs in New Jersey are:

What cities in New Jersey are hiring for Remote Tesla Machine Learning Engineer jobs?

Cities in New Jersey with the most Remote Tesla Machine Learning Engineer job openings:

Remote Tesla Machine Learning Engineer jobs near you
Infographic showing various Remote Tesla Machine Learning Engineer job openings in New Jersey as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

AI Solutions Architect - Remote

NAVA Software Solutions

Jersey City, NJ • On-site, Remote

$69 - $90.75/hr

Full-time

Re-posted 15 days ago

Job description

NAVA Software solutions is looking for a AI Solutions Architect
Details:
AI Solution Architect - Insurance Domain (Azure & AWS)
Location: Remote
Duration: 12 months
Role Overview
As an AI Solution Architect specializing in Azure and AWS, you will lead the design, development, and production deployment of large-scale AI/ML solutions tailored for the insurance industry. You will work closely with cross-functional teams including data scientists, engineers, actuaries, and business leaders to transform business strategy into secure, scalable, and cost-effective AI architectures.
Key Responsibilities
AI Strategy & Use Case Development
  • Identify and prioritize AI/ML use cases across the insurance value chain: Underwriting, pricing, claims fraud detection, customer segmentation, policy recommendation engines, and chatbots.
  • Partner with business stakeholders (e.g., actuaries, underwriters, claims analysts) to define impactful AI-driven solutions that enhance decision-making and operational efficiency.
Architecture & Design
  • Design resilient, scalable, and cloud-agnostic AI/ML architectures using Azure and AWS.
  • Build and manage data ingestion and transformation pipelines using Azure Data Factory and AWS Glue.
  • Define and implement MLOps workflows using Azure ML Pipelines, AWS SageMaker Pipelines, and MLflow.
Technical Leadership
  • Lead design reviews, technical workshops, and blueprint sessions.
  • Mentor engineers and data scientists in best practices for model development, deployment, and cloud-native AI.
Solution Development
  • Implement NLP, computer vision, and deep learning solutions using Azure Cognitive Services, AWS Comprehend, Rekognition, and Bedrock.
  • Develop microservices/APIs (Python, FastAPI) for real-time inference and batch scoring.
  • Work with frameworks like TensorFlow, PyTorch, and Scikit-learn.
Integration with Insurance Systems
  • Ensure seamless integration with core insurance platforms: Policy Administration, Claims Management, Billing, CRM (e.g., Guidewire, Duck Creek, Salesforce).
  • Collaborate with enterprise architects to align AI with broader IT modernization initiatives.

Deployment & Operations
  • Containerize models using Docker, deploy via Kubernetes (AKS/EKS).
  • Implement CI/CD automation (Azure DevOps, AWS CodePipeline) and observability (CloudWatch, Prometheus, Azure Monitor).
Governance & Security
  • Enforce cloud security and data compliance using IAM, VNet, KMS, and encryption protocols.
  • Leverage Azure Responsible AI and AWS SageMaker Clarify for explainability, fairness, and auditability.
Stakeholder Engagement
  • Present technical architectures and value propositions to C-level executives, claims directors, and underwriting heads.
  • Serve as the bridge between business needs and AI/ML capabilities.
Required Qualifications
Experience:
  • 8-10 years in AI/ML and software/system architecture.
  • 5+ years in solution/technical leadership roles.

Education:
  • Bachelor's in Computer Science, Data Science, or Engineering.
  • Master's or PhD in AI/ML preferred.

Cloud Expertise:
  • Azure: Azure ML, Cognitive Services, Data Factory, Databricks, Cosmos DB
  • AWS: SageMaker, Comprehend, Rekognition, Glue, Redshift, DynamoDB

Tools & Frameworks:
  • Languages: Python (mandatory), Java or C++
  • ML Frameworks: TensorFlow, PyTorch, Scikit-learn
  • Big Data & Streaming: Spark, Kafka, Hadoop
  • MLOps/DevOps: Kubernetes (AKS/EKS), Docker, MLflow, Kubeflow, CI/CD pipelines
Preferred Qualifications
  • Certifications: Azure AI Engineer Associate, AWS Certified Machine Learning - Specialty
  • Advanced AI Expertise: Generative AI (Azure OpenAI, ChatGPT, AWS Bedrock), Prompt Engineering, Agentic AI
  • Community & Research: Contributions to open-source projects or AI/ML publications
  • Soft Skills: Strong communication, stakeholder management, and strategic thinking. Team leadership and mentoring
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About NAVA Software Solutions

Sourced by ZipRecruiter

NAVA is a strategic partner for companies seeking to develop or customize software and products. Our team of experts leverages cutting-edge technology and deep industry knowledge to provide customized solutions that drive business success. Whether you're looking to improve your operations, increase efficiency, or bring a new product to market, NAVA has the expertise and resources to help you achieve your goals. Trust us to be your partner in software and product development.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Rocky Hill, CT, US

Social media

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