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Remote Applied Scientist Machine Learning Jobs (NOW HIRING)

Zillow

Sr. Applied Scientist

$152K - $244K/yr

... machine learning. You will build and scale routing and allocation decision systems that match ... This role has been categorized as a Remote position. "Remote" employees do not have a permanent ...

AppOmni

Lead Data Scientist

What We're Looking For * 7+ years of experience as a Data Scientist, Applied Scientist, Machine Learning Engineer, or similar role, with ownership of production data or decision systems. * Strong ...

Oracle

[Remote] Principal Applied Scientist

As our Principal Applied Scientist, you will play a key role in shaping the future of AI at Oracle ... Deep technical understanding of Machine Learning, Deep Learning architectures like Transformers ...

Zanskar

Senior Machine Learning Scientist

Salt Lake City, UT · On-site +1

$88K - $121K/yr

Salt Lake City, UT, Hybrid (3 days in office, 2 days can be remote) Benefits Eligible: Yes Manager ... What we're looking for 3+ years of applied ML experience, ideally in scientific ML, decision-making ...

Zanskar

Senior Machine Learning Scientist

Salt Lake City, UT · On-site +1

$88K - $121K/yr

Salt Lake City, UT, Hybrid (3 days in office, 2 days can be remote) Benefits Eligible: Yes Manager ... What we're looking for 3+ years of applied ML experience, ideally in scientific ML, decision-making ...

Webflow

Senior Staff Machine Learning Scientist, Assets

$93K - $127K/yr

Remote-first (United States; BC & ON, Canada) * Full-time * Permanent * Exempt * Our cash ... Partner closely with applied scientists, ML engineers, and product teams to move research from ...

Webflow

Senior Staff Machine Learning Scientist, Assets

OR · On-site +1

$91K - $124K/yr

Remote-first (United States; BC & ON, Canada) * Full-time * Permanent * Exempt * Our cash ... Partner closely with applied scientists, ML engineers, and product teams to move research from ...

Zillow

Senior Applied Scientist, Agentic AI

$152K - $244K/yr

This role has been categorized as a Remote position. "Remote" employees do not have a permanent ... Machine Learning * 2+ years of experience in building large-scale, high-impact ML solutions ...

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Remote Applied Scientist Machine Learning information

What does a Remote Applied Scientist in Machine Learning do?

A Remote Applied Scientist in Machine Learning develops and implements machine learning models to solve real-world problems, often from a location outside of a traditional office. Their work involves analyzing large datasets, designing algorithms, and collaborating with teams to deploy scalable solutions. They may also conduct experiments to improve model performance and stay up to date with the latest research in the field. Communication and documentation are important, as they often work with cross-functional teams remotely.

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

To thrive as a Remote Applied Scientist in Machine Learning, you need a strong background in mathematics, statistics, and computer science, often supported by an advanced degree and experience in ML algorithm development. Familiarity with programming languages like Python or R, machine learning frameworks such as TensorFlow or PyTorch, and tools for data processing and cloud computing is essential. Exceptional problem-solving ability, communication, and self-motivation are key soft skills for collaborating remotely and driving projects forward. These skills ensure you can independently design, implement, and communicate impactful machine learning solutions in a distributed work environment.

What can I expect in terms of collaboration and communication when working as a Remote Applied Scientist in Machine Learning?

As a Remote Applied Scientist in Machine Learning, you will frequently collaborate with cross-functional teams, including data engineers, product managers, and software developers. Communication typically takes place via video calls, chat platforms, and shared documentation, so strong written and verbal communication skills are essential. You may participate in regular virtual stand-ups, sprint planning, and code reviews to align on project goals and share progress. Remote work environments emphasize proactive communication and self-management to ensure seamless teamwork and project delivery.
What cities are hiring for Remote Applied Scientist Machine Learning jobs? Cities with the most Remote Applied Scientist Machine Learning job openings:
What are the most commonly searched types of Applied Scientist Machine Learning jobs? The most popular types of Applied Scientist Machine Learning jobs are:
What states have the most Remote Applied Scientist Machine Learning jobs? States with the most job openings for Remote Applied Scientist Machine Learning jobs include:
Remote Applied Scientist Machine Learning jobs near you

Senior Applied AI Scientist (remote)

Claritev

Manhattan, NY • On-site, Remote

Full-time

Posted 16 days ago

Job description

At Claritev, our mission is to simplify healthcare workflows, improve transparency, and bend the healthcare cost curve. We believe that data, technology, and AI can fundamentally transform how healthcare operates by automating complex workflows, improving decision-making, and reducing unnecessary costs across the system.

By combining deep healthcare expertise with advanced analytics and AI, we help payers, providers, and employers operate more efficiently and deliver better outcomes for the people they serve.

We are bold in our thinking, rigorous in execution, and committed to service excellence for every stakeholder. Our culture values innovation, accountability, diversity of thought, and collaboration.

Join us as we accelerate our transformation into a leading technology and AI-driven company shaping the future of healthcare.

JOB SUMMARY:

We are seeking a Senior Applied AI Scientist to lead the research, development, and deployment of advanced machine learning and AI systems that power Claritev's next generation of healthcare products.

This is a hands-on technical leadership role for an experienced applied scientist who thrives at the intersection of research innovation, real-world deployment, and measurable business impact. You will architect and deliver predictive, generative, and agentic AI systems that automate complex healthcare workflows and unlock new insights from large-scale healthcare data.

In this role, you will work closely with Product, Engineering, and business leaders to translate cutting-edge research into scalable production solutions that improve transparency, reduce costs, and simplify healthcare operations.

KEY RESPONSIBILITIES:
AI & Machine Learning

  • Design, develop, and deploy machine learning and AI models in production environments
  • Build predictive, generative, and optimization models to improve healthcare outcomes and operational efficiency
  • Improve existing models and systems with measurable impact on performance, scalability, or business metrics

Innovation & Applied Research

  • Research and evaluate emerging AI technologies, foundation models, and agentic systems to identify opportunities for new products and capabilities.
  • Design and implement novel machine learning and optimization methodologies tailored to complex healthcare data and workflows.
  • Drive experimentation and rapid prototyping to accelerate innovation and product development.

Product & Business Impact

  • Partner with Product, Engineering, and business stakeholders to translate AI capabilities into scalable solutions.
  • Identify opportunities to leverage Claritev's data assets to create new AI-driven products, insights, and automation capabilities.
  • Collaborate directly with clients to gather feedback and ensure solutions deliver measurable value.

Engineering & Production Excellence

  • Write high-quality, scalable, and production-ready code.
  • Work closely with Engineering and DevOps teams to deploy and maintain models in production systems.
  • Develop monitoring frameworks to ensure model performance, reliability, and data quality over time.

Collaboration

  • Collaborate cross-functionally with Product Managers, Engineers, Data Scientists, and domain experts
  • Contribute to team knowledge sharing, code reviews, and best practices
  • Provide guidance and informal mentorship to junior team members where appropriate

Governance & Compliance

  • Follow best practices for data privacy, security, and compliance (e.g., HIPAA)
  • Support model validation, monitoring, and responsible AI practices

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