Machine Learning Engineer Location: Long Island City, NY 11101 (Onsite 4 Days/week) Type: Permanent Full Time About the Role : In this role, you will take the lead in developing and fine-tuning ...
Machine Learning Engineer Location: Long Island City, NY 11101 (Onsite 4 Days/week) Type: Permanent Full Time About the Role : In this role, you will take the lead in developing and fine-tuning ...
Well, we are looking for a Machine Learning Engineer who will deliver business value by executing ... Calendly uses the zip code of an employee's remote work location, or the onsite building location ...
Well, we are looking for a Machine Learning Engineer who will deliver business value by executing ... Calendly uses the zip code of an employee's remote work location, or the onsite building location ...
Machine Learning Engineer
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Machine Learning Engineer
OR · Remote
$100K - $200K/yr
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$133K - $175K/yr
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$133K - $175K/yr
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Quick apply
Senior Machine Learning Engineer
Boston, MA · Remote
$125K - $165K/yr
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AI Pipeline Engineer/ Principal Machine Learning Engineer - REMOTE Strategic Initiatives Team Armis is seeking a talented and motivated AI Pipeline Engineer to join our Strategic Initiatives team.
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North, SC · On-site +1
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Remote Tesla Machine Learning Engineer information
See salary details
$31.5K - $46.2K
1% of jobs
$46.2K - $61K
1% of jobs
$61K - $75.7K
5% of jobs
$75.7K - $90.4K
6% of jobs
$102.6K is the 25th percentile. Wages below this are outliers.
$90.4K - $105.1K
14% of jobs
$105.1K - $119.9K
14% of jobs
The median wage is $127.2K / yr.
$119.9K - $134.6K
18% of jobs
$134.6K - $149.3K
14% of jobs
$152.3K is the 75th percentile. Wages above this are outliers.
$149.3K - $164K
12% of jobs
$164K - $178.8K
11% of jobs
$178.8K - $193.5K
5% of jobs
$31.5K
$128.8K
$193.5K
How much do remote tesla machine learning engineer jobs pay per year?
As of Jun 24, 2026, the average yearly pay for remote tesla machine learning engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.
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, and why are they important?
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?
| Aspect | Remote Tesla Machine Learning Engineer | Remote Data Scientist |
|---|---|---|
| Required Credentials | Degree in Computer Science, Engineering, or related field; experience with ML frameworks | Degree in Statistics, Mathematics, or related field; strong programming skills |
| Work Environment | Collaborates with engineering teams on autonomous systems and vehicle data | Analyzes large datasets to extract insights for business or product decisions |
| Employer & Industry Usage | Primarily in automotive, tech, and autonomous vehicle sectors | Across 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.
More about Remote Tesla Machine Learning Engineer jobs
What cities are hiring for Remote Tesla Machine Learning Engineer jobs? Cities with the most Remote Tesla Machine Learning Engineer job openings:
What are the most commonly searched types of Tesla Machine Learning Engineer jobs? The most popular types of Tesla Machine Learning Engineer jobs are:
What states have the most Remote Tesla Machine Learning Engineer jobs? States with the most job openings for Remote Tesla Machine Learning Engineer jobs include:
What job categories do people searching Remote Tesla Machine Learning Engineer jobs look for? The top searched job categories for Remote Tesla Machine Learning Engineer jobs are:
- Machine Learning Biomedical Engineer
- Senior Meta Machine Learning
- Google Machine Learning Engineer
- Online Machine Learning
- No Experience Nvidia Machine Learning
- Graduate Machine Learning Engineer
- Full Time No Experience Machine Learning
- Machine Learning Ops Engineer
- International Machine Learning Engineer
- Machine Learning Trainer
Full-time
This job post has expired today. Applications are no longer accepted.
Job description
Job Title: Machine Learning Engineer
Location: Long Island City, NY 11101
(Onsite 4 Days/week)
Type: Permanent Full Time
About the Role:
In this role, you will take the lead in developing and fine-tuning predictive ML models, with a primary focus on Ad Score and Ad Account Health.
Responsibilities include but are not limited to;
ML Model Development: Lead the development and refinement of predictive ML models, particularly Ad Score and Ad Account Health.
Data Analysis: Conduct in-depth data analysis to identify trends, patterns, and insights that inform model development and optimization.
Feature Engineering: Collaborate with data engineers to create and maintain feature engineering pipelines to support model training.
Model Evaluation: Implement rigorous evaluation methodologies to assess model performance, making necessary adjustments for continuous improvement.
Deployment and Integration: Work closely with engineering teams to deploy models and integrate them into our products through APIs.
Collaboration: Collaborate closely with product managers, full-stack engineers, and TPMs to ensure seamless integration of data science solutions into our products.
Research and Innovation: Stay up-to-date with the latest developments in the field of data science and machine learning, and explore innovative approaches to problem-solving.
Requirements
Required knowledge of:
Nice to have:
Data Transformation (dbt)
Semantic Layers (Cube, Looker, dbt Metrics)
TypeScript
Bayesian modeling experience - ideally Marketing Mix Models (PyMC, Stan, or similar..). Understands priors, MCMC sampling, posterior diagnostics.
Causal inference / experimentation- geo experiments (matched markets), A/B testing at scale. Familiar with incrementality measurement.
Marketing/advertising domain- understanding of attribution, media channels (paid social, search, display, video), campaign structures.
Nice to have - familiarity with adstock/saturation curves and budget optimization
Our interview process includes, but is not limited to the following:
Location: Long Island City, NY 11101
(Onsite 4 Days/week)
Type: Permanent Full Time
About the Role:
In this role, you will take the lead in developing and fine-tuning predictive ML models, with a primary focus on Ad Score and Ad Account Health.
Responsibilities include but are not limited to;
ML Model Development: Lead the development and refinement of predictive ML models, particularly Ad Score and Ad Account Health.
Data Analysis: Conduct in-depth data analysis to identify trends, patterns, and insights that inform model development and optimization.
Feature Engineering: Collaborate with data engineers to create and maintain feature engineering pipelines to support model training.
Model Evaluation: Implement rigorous evaluation methodologies to assess model performance, making necessary adjustments for continuous improvement.
Deployment and Integration: Work closely with engineering teams to deploy models and integrate them into our products through APIs.
Collaboration: Collaborate closely with product managers, full-stack engineers, and TPMs to ensure seamless integration of data science solutions into our products.
Research and Innovation: Stay up-to-date with the latest developments in the field of data science and machine learning, and explore innovative approaches to problem-solving.
Requirements
- Master's or Ph.D. in a related field with a strong academic background.
- Proven experience as a Data Scientist with a track record of developing and deploying predictive ML models.
- Expertise in machine learning techniques, including but not limited to regression, classification, clustering, and deep learning.
- Proficiency in data manipulation, feature engineering, and model evaluation.
- Strong programming skills in languages such as Python and experience with libraries like TensorFlow, PyTorch, or scikit-learn.
- Excellent communication skills and the ability to collaborate effectively within cross-functional teams.
- A passion for continuous learning and staying updated with the latest trends and technologies in data science.
- Strong problem-solving abilities and the capacity to translate complex data into actionable insights.
Required knowledge of:
- Python
- SQL
- Cloud Platforms (GCP, AWS, Azure)
- Data Warehouses (BigQuery, Snowflake, Redshift)
- LLMs / AI APIs
- Git / GitHub
Nice to have:
Data Transformation (dbt)
Semantic Layers (Cube, Looker, dbt Metrics)
TypeScript
Bayesian modeling experience - ideally Marketing Mix Models (PyMC, Stan, or similar..). Understands priors, MCMC sampling, posterior diagnostics.
Causal inference / experimentation- geo experiments (matched markets), A/B testing at scale. Familiar with incrementality measurement.
Marketing/advertising domain- understanding of attribution, media channels (paid social, search, display, video), campaign structures.
Nice to have - familiarity with adstock/saturation curves and budget optimization
Our interview process includes, but is not limited to the following:
About InstantServe
Sourced by ZipRecruiter
InstantServe provides a one-stop solution to all Healthcare, IT/Non-IT Staffing needs. Established in 2016, InstantServe is a strong workforce of over 100+ go-getters with a demonstrated background in IT/Non-IT service. We are a nationally certified SBE from the Department of Administration (State of PA). As a proud Minority Woman Owned Small Business Enterprise (M/WBE), InstantServe boasts of a strong team of professionals who have extensive experience catering to several Federal, Public, Commercial, and Healthcare Clients which includes 26 States and 46 government agencies. InstantServe is a client-centric organization that offers cost-effective and reliable solutions. Client satisfaction is sacrosanct! Our team strives to provide the best staffing and IT solutions to take your business to the next level.
Industry
Recruiting and staffing services
Company size
11 - 50 Employees
Headquarters location
Wayne, PA, US
Year founded
2016