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Ml Scientist Jobs (NOW HIRING)

General Motors

AI/ML Scientist

Milford, MI · On-site

You will work cross-functionally with engineers, data scientists, simulation specialists, domainexpertsand platform teams to define and execute high-impact AI/ML initiatives. Your role will blend ...

Manifold Bio

AI/ML Scientist

Boston, MA · On-site

$140K - $225K/yr

Mentor and guide junior scientists and engineers in advanced ML techniques and research methodologies * Drive strategic research planning and identify promising new directions for AI-driven drug ...

Wispr Flow

ML Scientist

San Francisco, CA · On-site

$185K - $280K/yr

About the Role As a ML scientist at Wispr, you'll play a crucial role in building the first capable, habit forming voice interface that scales to a billion users. Members of our technical staff are ...

Cleerly

Sr. ML Scientist

Boston, MA · On-site

In this role, you will collaborate with ML scientists, data engineers, biostatisticians, regulatory experts, and senior leadership to understand clinical requirements, develop innovative solutions ...

insitro

(Senior) ML Scientist

South San Francisco, CA · On-site

$183K - $238K/yr

Ph.D. in computer science, machine learning, computational biology, systems biology, or a related discipline. * Extensive hands on experience developing ML methods for biological data modalities

Axle

AI/ML Scientist/Developer

Frederick, MD · On-site

$115K - $130K/yr

Axle is seeking a AI/ML Scientist/Developer to join our vibrant team at the National Institutes of Health (NIH) supporting the Standardized Organoid Model Center in Frederick, MD. The Standardized ...

Axle

AI/ML Scientist/Developer

Frederick, MD · On-site

They are seeking an AI/ML Scientist/Developer to develop innovative computational models to predict and optimize organoid growth and differentiation protocols. Responsibilities : • The successful ...

Axle

AI/ML Scientist/Developer

Frederick, MD

$115K - $130K/yr

Axle is seeking a AI/ML Scientist/Developer to join our vibrant team at the National Institutes of Health (NIH) supporting the Standardized Organoid Model Center in Frederick, MD. The Standardized ...

Axle

AI/ML Scientist/Developer

Frederick, MD · On-site

Axle is seeking a AI/ML Scientist/Developer to join our vibrant team at the National Institutes of Health (NIH) supporting the Standardized Organoid Model Center in Frederick, MD. The Standardized ...

Axle

AI/ML Scientist/Developer

Frederick, MD · On-site

They are seeking an AI/ML Scientist/Developer to develop innovative computational models to predict and optimize organoid growth and differentiation protocols. Responsibilities : • The successful ...

Axle

AI/ML Scientist/Developer

Frederick, MD · On-site

They are seeking an AI/ML Scientist/Developer to develop computational models for organoid growth and differentiation, contributing to the Standardized Organoid Model Center at the NIH.

lululemon

Applied AI/ML Scientist

Seattle, WA · On-site

Core responsibilities As an Applied AI/ML Scientist, you design, develop, test, and optimize AI/ML solutions that address defined business problems, with an emphasis on applied modeling ...

SentiLink

Staff Applied ML Scientist

As a Staff Applied ML Scientist, you will build core products that identify fraudsters and advance financial risk products, requiring deep domain understanding and strong technical abilities.

ECS

Principal AI/ML Scientist

Arlington, VA · On-site

$140K - $180K/yr

Everforth ECS is seeking a Principal AI/ML Scientist to work in our Arlington, VA office. Everforth ECS Federal is seeking an experienced Principal AI/ML Scientist to design, develop, and deploy AI ...

SentiLink

Senior Applied ML Scientist

As a Senior Applied ML Scientist, you will build core products that identify fraudsters and advance the company's suite of products in financial risk, requiring deep domain understanding and strong ...

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Ml Scientist information

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$12

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How much do ml scientist jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for ml scientist in the United States is $57.49, according to ZipRecruiter salary data. Most workers in this role earn between $38.70 and $73.80 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an ML Scientist, and why are they important?

To thrive as an ML Scientist, you need strong knowledge of machine learning algorithms, statistics, and programming languages like Python or R, typically supported by an advanced degree in computer science, mathematics, or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and tools for data manipulation and visualization is crucial, along with experience using cloud platforms like AWS or Azure. Excellent problem-solving, critical thinking, and communication skills help translate complex data insights into actionable business solutions. These skills ensure the effective development, deployment, and interpretation of machine learning models that drive innovation and informed decision-making.

What is the difference between Ml Scientist vs Data Analyst?

AspectML ScientistData Analyst
Required CredentialsMaster's or PhD in Computer Science, Data Science, or related fields; strong programming skillsBachelor's degree in Statistics, Mathematics, or related fields; proficiency in data visualization tools
Work EnvironmentResearch-focused, developing models, experimenting with algorithmsData cleaning, reporting, and interpreting data for business insights
Industry UsageTech companies, research institutions, AI developmentBusiness, marketing, finance, healthcare sectors

ML Scientists focus on developing and refining machine learning models using advanced algorithms, often working in research or AI development environments. Data Analysts primarily interpret data to generate reports and insights for business decision-making. While both roles require strong analytical skills, ML Scientists typically have more technical credentials and work on complex modeling tasks, whereas Data Analysts focus on data interpretation and visualization for practical applications.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data processing, and system integration. While AI automation tools can assist with certain tasks, MLEs are essential for building complex, customized solutions and maintaining AI systems, making complete replacement unlikely in the near term.

What are ML Scientists?

ML Scientists, or Machine Learning Scientists, are professionals who research, design, and develop algorithms that enable computers to learn from and make predictions or decisions based on data. They often work at the intersection of computer science, statistics, and domain expertise to solve complex problems using machine learning techniques. Their responsibilities may include building and optimizing models, conducting experiments, analyzing results, and collaborating with engineers and data scientists to deploy solutions. ML Scientists are employed in various industries, such as technology, healthcare, finance, and more, where they help drive innovation by leveraging data.

Which 3 jobs will survive AI?

For an ML Scientist, roles that require complex problem-solving, creativity, and domain expertise are more likely to persist alongside AI advancements. These include jobs in strategic research, ethical AI development, and specialized data analysis, which demand human judgment and nuanced understanding beyond automation. Continuous learning and skills in programming, statistics, and domain knowledge are essential to stay relevant as AI evolves.

What are some common challenges ML Scientists face when deploying models to production environments?

ML Scientists often encounter challenges when transitioning models from research to production, such as ensuring model scalability, maintaining data consistency, and addressing performance degradation over time. Collaborating closely with data engineers and software developers is essential to integrate models seamlessly into existing systems. Additionally, monitoring deployed models for concept drift and retraining needs is a critical responsibility to maintain accuracy and reliability in real-world applications.

What does an ML scientist do?

An ML scientist develops and implements machine learning models to solve complex problems using large datasets. They analyze data, select appropriate algorithms, and optimize models, often using tools like Python, R, or TensorFlow. Their work supports data-driven decision-making across various industries.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position such as a senior machine learning scientist or AI executive that offers a total compensation package including salary, bonuses, and stock options. These roles often require advanced skills in deep learning, data analysis, and experience with tools like TensorFlow or PyTorch, along with a strong educational background and industry experience. Such compensation is usually found in leading tech companies or startups with significant AI investments.
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Ml Scientist jobs near you
Infographic showing various Ml Scientist job openings in the United States as of July 2026, with employment types broken down into 96% Full Time, 2% Part Time, and 2% Contract. Highlights an 82% Physical, 4% Hybrid, and 14% Remote job distribution, with an average salary of $119,587 per year, or $57.5 per hour.
Senior Applied AI/ML Scientist - Fulfillment

Senior Applied AI/ML Scientist - Fulfillment

Faire

San Francisco, CA

$196K - $269K/yr

Other

Re-posted 18 days ago

Job description

About this role

Faire leverages the power of machine learning (ML) and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores. Our highly skilled team of Applied AI/ML Scientist and machine learning engineers specialize in developing algorithmic solutions for notification and recommender systems, advertising attribution, and Lifetime Value (LTV) predictions. Our ultimate goal is to empower local retail businesses with the tools they need to succeed.

At Faire, the Data team is responsible for creating and maintaining a diverse range of algorithms and models that power our marketplace. We are dedicated to building machine learning models that help our customers thrive.

As an Applied AI/ML Scientist on the Retailer team, you'll tackle a diverse set of challenges, such as optimizing logistics and freight costs and calculating optimal credit limits. You'll also contribute to growing Faire's retailer base by enhancing Search Engine Optimization, personalizing landing pages for new retailers, and predicting retailer lifetime value. You'll collaborate closely with other Applied AI/ML Scientist, engineers, and product managers to drive projects that unlock value from our unique, rich, and rapidly growing two-sided marketplace data.

Our team already includes experienced Applied AI/ML Scientist and Machine Learning Engineers from Uber, Airbnb, Square, Facebook, and Pinterest. Faire will soon be known as a top destination for Applied AI/ML Scientist and machine learning, and you will help take us there! 

What you'll do 

  • Shipping cost optimization: Build ML models that provide accurate shipping cost estimates. Engineer new features to improve model performance. These models may use live carrier information and be both performant and explainable.
  • Fulfillment: Fulfillment has the potential to improve wholesale buying for both retailers and brands by an order of magnitude. This role involves building ML models to forecast demand for the SKUs we should stock in our warehouses, and applying predictive models to optimize shipping logistics-improving reliability while reducing costs.

Qualifications

  • An advanced degree (MS or PhD) in a relevant discipline such as statistics, economics, econometrics, mathematics, computer science, operations research, etc.
  • Strong machine learning skills and 3+ years of experience productionizing machine learning models (Sklearn, XGBoost, or Deep Learning)
  • Strong programming skills (Python, Java, Kotlin, C++)
  • Knowledge of statistical techniques such as experimentation and causal inference
  • SQL or other database querying experience preferred
  • An excitement and willingness to learn new tools and techniques

Salary Range

San Francisco: the pay range for this role is $196,000 to $269,500 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

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