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Senior Machine Learning Scientist Jobs (NOW HIRING)

Sr Machine Learning Scientist

Thousand Oaks, CA · On-site

$96K - $131K/yr

Machine Learning Scientist What you will do Let's do this. Let's change the world. Within Amgen's Research and Development organization, the Therapeutic Protein Design (TPD) team supports the broad ...

Senior Machine Learning Scientist

Scottsdale, AZ · On-site

$92K - $125K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI ... PhD and with +5 years for ML Scientist, +8 years for Sr. ML Scientist, +10 years for Principal ML ...

$78K - $107K/yr

Machine Learning Scientist What you will do Let'sdo this.Let'schange the world.Within Amgen's Research and Development organization, the Therapeutic Protein Design (TPD) team supports the broad goal ...

... modeling, and machine learning. Aligned and partnering with product verticals, we use this ... In Data Science & Analytics, you will contribute to horizontal ML systems and infrastructure that ...

You Have: * 5+ years of industry experience in prototyping and building scalable machine learning ... Science, Applied Math, Physics, Engineering, or other quantitative fields. For roles that are based ...

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Senior Machine Learning Scientist information

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$66.5K

$110.5K

$164.5K

How much do senior machine learning scientist jobs pay per year?

As of Jul 24, 2026, the average yearly pay for senior machine learning scientist in the United States is $110,545.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,500.00 and $125,000.00 per year, depending on experience, location, and employer.

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

AspectSenior Machine Learning ScientistData Scientist
CredentialsMaster's or PhD in CS, ML, or related fieldBachelor's or Master's in CS, Statistics, or related field
Work EnvironmentFocus on developing ML models, algorithms, and researchData analysis, visualization, and business insights
Industry UsageUsed in AI-driven companies, tech firms, research labsCommon across industries for data analysis and reporting

While both roles involve working with data, Senior Machine Learning Scientists focus on developing advanced ML models and algorithms, often requiring research and deep technical expertise. Data Scientists typically analyze data to generate insights and support decision-making. The roles overlap but differ mainly in technical depth and focus area.

What are Senior Machine Learning Scientists?

Senior Machine Learning Scientists are experienced professionals who design, develop, and implement advanced machine learning models to solve complex business or research problems. They are responsible for leading projects, mentoring junior team members, and staying updated on the latest AI and data science technologies. Their work often involves analyzing large datasets, selecting the right algorithms, and optimizing model performance for real-world applications. In addition to technical expertise, they often collaborate cross-functionally to align machine learning solutions with organizational goals.

What are the key skills and qualifications needed to thrive as a Senior Machine Learning Scientist, and why are they important?

To thrive as a Senior Machine Learning Scientist, you need expertise in machine learning algorithms, statistical analysis, programming (usually in Python or R), and an advanced degree (often a Ph.D.) in a quantitative field. Experience with tools such as TensorFlow, PyTorch, scikit-learn, cloud platforms, and version control systems is typically expected, along with knowledge of deploying models in production environments. Exceptional problem-solving, communication, and leadership skills help you translate complex data insights into actionable business solutions and mentor junior team members. These skills are crucial for developing innovative models, ensuring robust deployment, and driving impactful data-driven decisions.

What are some common challenges Senior Machine Learning Scientists face when deploying models to production environments?

Senior Machine Learning Scientists often encounter challenges such as ensuring model scalability, maintaining model performance over time, and addressing data drift once models are deployed to production. Collaborating closely with engineering and operations teams is crucial to streamline deployment pipelines and monitor models for real-world reliability. It’s also important to communicate findings and potential risks to stakeholders, and to regularly update models based on new data or business requirements. These aspects make strong cross-functional teamwork and problem-solving skills essential in this role.
More about Senior Machine Learning Scientist jobs
What cities are hiring for Senior Machine Learning Scientist jobs? Cities with the most Senior Machine Learning Scientist job openings:
What are the most commonly searched types of Machine Learning Scientist jobs? The most popular types of Machine Learning Scientist jobs are:
What states have the most Senior Machine Learning Scientist jobs? States with the most job openings for Senior Machine Learning Scientist jobs include:
Infographic showing various Senior Machine Learning Scientist job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $110,545 per year, or $53.1 per hour.
Senior Machine Learning Scientist

Senior Machine Learning Scientist

Teladoc

Concord, NC

Full-time

Posted 16 days ago


Job description

Join the team leading the next evolution of virtual care.

At Teladoc Health, you are empowered to bring your true self to work while helping millions of people live their healthiest lives.

Here you will be part of a high-performance culture where colleagues embrace challenges, drive transformative solutions, and create opportunities for growth. Together, we're transforming how better health happens.

Summary of Position

The Machine Learning effort is part of the Data Science team at Teladoc Health. In this role, you will partner with Product, Engineering, Clinical,Operations, Marketing and Data Engineering to design, build, deploy, andoperatescalable machine learning and AI systems that power business-critical decision making. You will own the end-to-end machine learning lifecycle:from data and feature engineering through deployment, monitoring, experimentation, and continuous improvement(across both batch and real-time production environments).Your efforts and contributions willhavea big impactonimproving member and provider experience on the Teladoc Health platform.

This is an opportunity to apply technical rigor, scalable data processing tools, and machine learning algorithms to solve real-world business problems while engineering, deploying, measuring, and iterating machine learning solutions in production.

Essential Duties and Responsibilities

  • Build production ready time series models to predict real time KPIs as well as build optimal decision actions to manage the provider network for clinical operations business optimization

  • Propose, evaluate and interpret the results of your work for clinical, product and business decision-makers and own outcomes

  • Collaborate closely with peers and stakeholders to discover and distill requirements of problem definitions, product features and architecture to improve clinical outcomes using insights and models

  • Develop modular, well-tested, production-quality software using Python, Spark and SQL to build scalable data engineering, feature engineering, machine learning and AI pipelines following software engineering best practices.

  • Design, develop, deploy and operate scalable production machine learning and AI systems, including data transformation pipelines, feature pipelines, model training, evaluation, deployment, monitoring, retraining, and experiment tracking. Ensure robust model lifecycle management through model versioning, MLflow, automated testing, CI/CD, and production monitoring.

  • Build and optimize scalable Spark and Databricks workloads, leveraging distributed computing best practices for large-scale data processing and real-time inference.

  • Design, evaluate and integrate Large Language Models (LLMs), retrieval-augmented generation (RAG), agentic workflows, and other AI capabilities where appropriate to solve business problems.

  • Monitor production models and data pipelines for data quality, feature drift, concept drift, latency, reliability, and business performance, proactively identifying and resolving issues.

Qualifications Expected for Position

  • 8+ years of experience as a Machine Learning Scientist, Data Scientist or in a similar role within SaaS or consumer technology companies.

  • A Master's degree or higher in computer science, operations research, machine learning, information systems, engineering, or a related field

  • Demonstrated depth of experience developing clean, robust, and reusable production-quality code using Python, Spark, and SQL.

  • Extensive experience designing, building and operating production machine learning systems, including scalable software, distributed data processing, reusable feature engineering pipelines, model deployment, monitoring and continuous improvement.

  • Strong understanding of statistical modeling, machine learning algorithms, experimentation, model evaluation, forecasting, and explainability techniques, with the ability to select appropriate approaches based on business and technical constraints.

  • Excellent data analysis skills and bias to deliver, measure and iterate using experimentation and statistical analysis

  • Strong system design skills with the ability to architect scalable, maintainable, and observable machine learning solutions.

  • Ability to translate machine learning solutions into measurable business outcomes and effectively communicate technical decisions, tradeoffs, and expected value to both technical and business stakeholders.

Bonus Qualifications

  • Hands-on experience with modern data and ML platforms such as Databricks, MLflow, Delta Lake, Airflow, Terraform, or equivalent cloud-native technologies.

  • Experience building AI-powered applications using Large Language Models (LLMs), embeddings, vector databases, retrieval-augmented generation (RAG), agentic workflows, or equivalent AI technologies is highly desirable.

  • Experience applying machine learning, forecasting, optimization, or decision science techniques to large-scale operational, logistics, marketplace, or network optimization problems.

  • Experience working with healthcare data (e.g., claims or EHR) is a plus.

  • Great active listening skills to infer product/business needs and underlying context.

  • Ability to collaborate effectively with peers, and respect for member privacy.

The base salary range for this position is$150,000 - $175,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2026.Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications.This information is applicable for all full-time positions.

#LI-SS2 #LI-Remote

We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. All time off must be approved by your manager prior to use. You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. This applies to full-time positions only. If you are applying for a part-time role, your recruiter can provide additional details.

As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. Applicants who falsify information will be disqualified.

Teladoc Health will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

Why join Teladoc Health?

  • Teladoc Health is transforming how better health happens. Learn how when you join us in pursuit of our impactful mission.

  • Chart your career path with meaningful opportunities that empower you to grow, lead, and make a difference.

  • Join a multi-faceted community that celebrates each colleague's unique perspective and is focused on continually improving, each and every day.

  • Contribute to an innovative culture where fresh ideas are valued as we increase access to care in new ways.

  • Enjoy an inclusive benefits program centered around you and your family, with tailored programs that address your unique needs.

  • Explore candidate resources with tips and tricks from Teladoc Health recruiters and learn more about our company culture by exploring #TeamTeladocHealth on LinkedIn.

As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status, or pregnancy). In our innovative and inclusive workplace, we prohibit discrimination and harassment of any kind.

Teladoc Health respects your privacy and is committed to maintaining the confidentiality and security of your personal information. In furtherance of your employment relationship with Teladoc Health, we collect personal information responsibly and in accordance with applicable data privacy laws, including but not limited to, the California Consumer Privacy Act (CCPA). Personal information is defined as: Any information or set of information relating to you, including (a) all information that identifies you or could reasonably be used to identify you, and (b) all information that any applicable law treats as personal information. Teladoc Health's Notice of Privacy Practices for U.S. Employees' Personal information is available at this link.


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About Teladoc

Sourced by ZipRecruiter

Industry

Fitness and sports centers

Company size

1,001 - 5,000 Employees

Headquarters location

New York, NY, US

Year founded

2002