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Senior Tesla Machine Learning Engineer Jobs in Newark, NJ

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

About the Role We are looking for a Senior Machine Learning Engineer, MLOps to help operationalize and scale our machine learning systems. This is an engineering-focused role centered on building the ...

REQUIREMENTS Requires a bachelor's degree in computer science, engineering, data science or machine learning plus 2 years of experience as a machine learning engineer. Must also possess: 2 years ...

Senior Machine Learning Engineer

Brooklyn, NY · On-site +1

$130K - $200K/yr

We are looking for a machine learning engineer to design, build, experiment and optimize Shaped's AI discovery engine. You will be a founding engineer that works on cutting-edge technologies and ...

They are seeking Machine Learning Engineers to build a platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to the development of core technology and ...

We are looking for a machine learning engineer to design, build, experiment and optimize Shaped's AI discovery engine. You will be a founding engineer that works on cutting-edge technologies and ...

Senior Machine Learning Engineer

Manhattan, NY · On-site

$133K - $176K/yr

Our client is a public safety product that's looking to add a machine learning engineer to their team. This particular role is focused on NLP/NLU for their real-time audio translation team. If you're ...

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining high quality, owning end-to-end ML pipelines while shaping product features that deliver real-world ...

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining high quality, owning end-to-end ML pipelines while shaping product features that deliver real-world ...

Senior Machine Learning Engineer

Manhattan, NY · On-site

$133K - $176K/yr

Our client is a public safety product that's looking to add a machine learning engineer to their team. This particular role is focused on NLP/NLU for their real-time audio translation team. If you're ...

We are seeking a highly adaptable, creative, and well‑rounded Machine Learning Engineer to join our team. You will own the end‑to‑end ML lifecycle, from dataset creation and foundational ...

Join our mission to infuse cutting-edge AI/ML/GenAI into pharmacy benefits as a Senior Machine Learning Engineer. We are looking for an experienced software engineer with machine learning expertise ...

We are seeking an analytical and innovative Senior Machine Learning Engineer to join our Data & AI team. You will play a key role in developing and deploying advanced machine learning models to solve ...

Showing results 41-60

Senior Tesla Machine Learning Engineer information

See Newark, NJ salary details

$62.2K

$132.3K

$191.9K

How much do senior tesla machine learning engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for senior tesla machine learning engineer in Newark, NJ is $132,344.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,300.00 and $150,100.00 per year, depending on experience, location, and employer.

What does a senior Tesla machine learning engineer do?

A Senior Tesla Machine Learning Engineer leads the development and deployment of advanced machine learning models to improve Tesla’s products, such as Autopilot, Full Self-Driving, and manufacturing optimization. They collaborate with multidisciplinary teams to collect data, design algorithms, and ensure models are robust and scalable. In this role, engineers are expected to mentor junior staff, drive research initiatives, and help translate cutting-edge AI advancements into real-world Tesla applications.

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

To thrive as a Senior Tesla Machine Learning Engineer, you need deep expertise in machine learning algorithms, strong programming skills in Python or C++, and a proven track record in deploying models at scale, often supported by an advanced degree in computer science or a related field. Familiarity with frameworks such as TensorFlow or PyTorch, experience working with large datasets, and cloud computing platforms are typically required, as well as knowledge of Tesla's proprietary systems. Exceptional problem-solving, collaboration, and communication skills distinguish top performers in this role. These abilities are crucial for developing advanced AI solutions that power Tesla's autonomous systems and for driving innovation in a highly competitive, fast-evolving environment.

How does a senior Tesla machine learning engineer typically collaborate with cross-functional teams?

As a Senior Machine Learning Engineer at Tesla, you will frequently work alongside software developers, data scientists, product managers, and hardware engineers. Collaboration is highly cross-functional, with regular meetings to align on project goals, data requirements, and model deployment strategies. You may be involved in translating business objectives into machine learning solutions, sharing insights with non-technical stakeholders, and refining algorithms based on feedback from various departments. This collaborative environment fosters innovation and ensures that machine learning models are well-integrated into Tesla's products and systems.

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

AspectSenior Tesla Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models for autonomous vehicles, energy, and manufacturingAnalyzes data to extract insights, supports product and business decisions
Employer & Industry UsageTesla, automotive, energy, AI projectsVarious industries including tech, finance, healthcare

While both roles involve working with data and algorithms, the Senior Tesla Machine Learning Engineer focuses on developing and deploying machine learning models for Tesla's products, especially autonomous systems. In contrast, a Data Scientist primarily analyzes data to inform business decisions across various industries. The ML Engineer role requires deeper expertise in machine learning frameworks and deployment, whereas Data Scientists focus more on statistical analysis and data visualization.

What are popular job titles related to Senior Tesla Machine Learning Engineer jobs in Newark, NJ?

For Senior Tesla Machine Learning Engineer jobs in Newark, NJ, the most frequently searched job titles are:

What job categories do people searching Senior Tesla Machine Learning Engineer jobs in Newark, NJ look for?

The top searched job categories for Senior Tesla Machine Learning Engineer jobs in Newark, NJ are:

What cities near Newark, NJ are hiring for Senior Tesla Machine Learning Engineer jobs?

Cities near Newark, NJ with the most Senior Tesla Machine Learning Engineer job openings:

Infographic showing various Senior Tesla Machine Learning Engineer job openings in Newark, NJ 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, with an average salary of $132,344 per year, or $63.6 per hour.

Senior Machine Learning Engineer

exacare ai

New York, NY • On-site

$114K - $157K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 6 days ago


Job description

About the Role
We are looking for a Senior Machine Learning Engineer, MLOps to help operationalize and scale our machine learning systems. This is an engineering-focused role centered on building the workflows, infrastructure, and processes that enable ML to move from research into reliable production systems.
You will partner closely with research-oriented ML teammates and help turn their work into scalable, maintainable, and cost-effective production systems. This includes building and improving data pipelines, training pipelines, deployment workflows, monitoring systems, and supporting infrastructure that allow the team to move faster and operate ML systems with confidence.
This is not a research-first role. It is best suited for someone who is excited by the systems, tooling, and operational side of machine learning.
What You'll Do
  • Build and maintain the workflows and infrastructure that support the end-to-end ML lifecycle
  • Partner with researchers and ML practitioners to productionize models and enable faster iteration
  • Design, build, and improve data pipelines and training pipelines
  • Improve data processing, annotation workflows, and ML system efficiency
  • Deploy and maintain the background systems that support model training and inference
  • Build tooling and processes for monitoring model performance, system reliability, and operational health
  • Improve the scalability, observability, and reproducibility of ML systems
  • Optimize ML infrastructure for speed, reliability, and cost-efficiency
  • Identify bottlenecks in the ML workflow and automate or streamline manual processes
  • Help establish best practices around ML operations, deployment, and system performance

What You'll Bring
  • Several years of experience in machine learning engineering, MLOps, ML infrastructure, data engineering, or backend/platform engineering in ML environments
  • Experience supporting ML systems end to end, from model handoff through deployment and monitoring
  • Strong experience building and owning data pipelines, training pipelines, or other production workflows that support ML
  • Experience working closely with researchers, data scientists, or ML practitioners to productionize models
  • Strong software engineering fundamentals and experience building production systems
  • Experience with monitoring, debugging, and improving production ML or data systems
  • A track record of improving reliability, scalability, speed, and/or cost efficiency in ML systems
  • Comfort operating in a fast-moving, startup-style environment with a high degree of ownership

Benefits + Perks
  • Competitive salary and equity in a high-growth startup
  • Flexible PTO, take what you need
  • Medical, dental, and vision coverage
  • Great startup culture, including company off-sites
  • High-achieving team, including ex-Amazon engineers and alumni of Bain, BCG, Goldman Sachs, and more

An insight into our Core Values
Only the best belong here
We are unapologetic about talent. This should be the best team you have ever been on. Protecting that standard is how we honor each other's time, ambition, and craft.
We work even harder to keep our partners than we did to earn them initially
The work does not stop when a customer first onboards to our platform. It deepens over time. We partner with operators, listening and learning about real problems, and translate that into solutions that help them succeed in practice. We earn trust through consistent delivery.
We keep the patient downstream of every decision
At the end of the day, this is about the patient. We get there by deeply respecting and reflecting on our purpose: to develop software that aids teams in delivering better care.
Raise the bar on ownership
We grow because people here go beyond the minimum. We invest extra effort, care, and ownership into what we build.
The world is moving fast. We move faster.
This is a race. We work hard, we move early, and we stay ahead of problems and competitors. If we slow down, someone else will pass us.
Radical candor, zero politics
We say what's true, early, and we keep communication direct and clean so the team can move.
Bring good vibes and win together
We win as a team. We bring energy, support each other, and make the workplace somewhere people are excited to show up.
If this sounds like you, we'd love to have a chat!
#LI-Hybrid
About exacare ai
exacare ai is a leading health tech company on a mission to build the AI operating system for post-acute care. Our platform turns messy, unstructured referral packets into clear clinical insights and next steps, so teams can make faster, safer placement decisions with less administrative burden. Today, exacare ai powers more than 2,000 facilities, and is growing rapidly.
We recently raised a $30M Series A led by Insight Partners, and are bringing world-class talent together to transform healthcare. If you like building, learning, and want to make a real impact, come join us!