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Senior Applied AI Scientist

Remote from
USA flag
USA
Salary, yearly, USD
120,000 - 150,000
Employment type
Full Time,
Job posted
Apply before
9 Jun 2026
Experience level
Senior
Views / Applies
686 / 170

About Claritev

Transforming healthcare through innovative solutions.

Actively Hiring
Verified job posting
This job post has been manually reviewed for authenticity and compliance.

AI Summary

Claritev is seeking a Senior Applied AI Scientist to lead the development of advanced ML and AI systems for healthcare. The role involves designing predictive, generative, and agentic AI solutions to automate workflows and improve transparency. Candidates need a PhD/MS in a relevant field, 3-6 years of industry experience, and 1-2 years in generative AI. The position offers a salary range of $120,000-$150,000 per year. This role is based in the US and requires expertise in healthcare AI.

Job Complexity

Easy Hard
AI Insight The role requires a high level of expertise in AI/ML, including generative AI, and experience in healthcare, which adds complexity. The combination of research, production deployment, and cross-functional collaboration makes it challenging.

Salary Analysis

Median
USD135,000
US Market
USD130,000 – USD200,000
AI Insight The offered salary range of $120,000-$150,000 is competitive for a Senior Applied AI Scientist, though slightly below the top end of the market. The median of $135,000 is reasonable for a role requiring 3-6 years of experience and healthcare domain knowledge.

Key Skills

Machine Learning Generative AI Healthcare Predictive Modeling Natural Language Processing Python Deep Learning Data Science Agentic AI Production Deployment

Dear Hiring Manager,

I am excited to apply for the Senior Applied AI Scientist position at Claritev. With a PhD in Computer Science and over 5 years of experience in developing and deploying machine learning models in healthcare, I am confident in my ability to drive innovation and deliver impactful AI solutions. My expertise in generative AI and agentic systems aligns perfectly with your mission to transform healthcare workflows.

In my previous role at a health tech company, I led the development of a predictive model that reduced administrative costs by 20% and automated key processes. I am skilled in taking research from prototype to production, ensuring scalability and compliance with HIPAA. I thrive in cross-functional teams and am passionate about using AI to improve healthcare outcomes.

I look forward to the opportunity to contribute to Claritev's AI-driven transformation. Thank you for your consideration.

Sincerely, [Your Name]

Describe a time you deployed a machine learning model from prototype to production. What challenges did you face and how did you overcome them?
In my previous role, I developed a predictive model for patient readmission risk. The main challenge was ensuring real-time inference with low latency. I optimized the model using quantization and implemented a microservice architecture with Docker and Kubernetes. I also set up monitoring to track model drift and retrained the model monthly.
How would you approach building a generative AI system for automating healthcare documentation?
I would start by fine-tuning a large language model on de-identified clinical notes, ensuring HIPAA compliance. I'd use retrieval-augmented generation to incorporate patient-specific data from EHRs. The system would be designed with human-in-the-loop validation to ensure accuracy. I'd also implement robust data privacy measures and monitor for biased outputs.
Explain a complex machine learning concept to a non-technical stakeholder. How do you ensure they understand the value?
I would use an analogy, like comparing a recommendation system to a personalized shopping assistant. I'd focus on the business impact: how it improves efficiency or reduces costs. I avoid jargon and use visualizations to show performance metrics. I also ask for feedback to confirm understanding.
What experience do you have with agentic AI systems? Can you describe one you built?
I built an agentic system for automated claims processing. The agent used reinforcement learning to decide the sequence of steps: verify patient info, check coverage, and apply rules. It interacted with multiple APIs and used a reward function to minimize processing time. The system reduced manual effort by 30%.
How do you ensure your models are fair and unbiased, especially in healthcare?
I start by auditing training data for representation across demographic groups. I use fairness metrics like equal opportunity and demographic parity. During development, I test models on subgroups and adjust thresholds if needed. I also implement monitoring for disparate impact post-deployment and involve domain experts to review outcomes.

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

Qualifications

JOB REQUIREMENTS

  • Ph.D. or M.S. in Computer Science, Statistics, Applied Mathematics, Data Science, or a related field.
  • 3–6 years of experience post-MS, or 0–3 years post-PhD applying Machine Learning (ML), Predictive Modeling, or Generative/Agentic AI in industry, with a proven track record of delivering solutions from prototype to production.
  • 1-2 years of hands-on experience with Generative AI and agent development.
  • Healthcare or health services experience is a plus
  • Strong proficiency in Python, deep learning frameworks (e.g., PyTorch, TensorFlow), and agentic frameworks (e.g. LangChain, LangGraph, Autogen, crewAI, n8n).
  • Expertise in designing and implementing RAG pipelines, and integrating planning, memory, tools, MCP, and A2A protocol for agent workflows.
  • Experience in building evaluation pipelines for LLM and agent performance, including metrics such as accuracy, reliability, and latency.
  • Proficiency in using AI Coding tools like Github Copilot, OpenAI Codex etc. 
  • Strong foundation in ML theory, including deep learning, statistics, or optimization.
  • A product-oriented mindset, with the ability to align applied science work with business objectives and impact.
  • Excellent communication and cross-functional collaboration skills.

COMPENSATION

The salary range for this position is $120K to $150K. Specific compensation offers are determined based on a variety of factors including the candidate’s education, experience, skills, work location, and internal equity considerations. In addition to base salary, this position is eligible for an annual performance bonus and a comprehensive benefits package, including health insurance and a 401(k) retirement plan.

BENEFITS

We realize that our employees are instrumental to our success, and we reward them accordingly with very competitive compensation and benefits packages, an incentive bonus program, as well as recognition and awards programs. Our work environment is friendly and supportive, and we offer flexible schedules whenever possible, as well as a wide range of live and web-based professional development and educational programs to prepare you for advancement opportunities.

Your benefits will include:

  • Medical, dental and vision coverage with low deductible & copay
  • Life insurance
  • Short and long-term disability
  • Paid Parental Leave
  • 401(k) + match
  • Employee Stock Purchase Plan
  • Generous Paid Time Off – accrued based on years of service
    • WA Candidates: the accrual rate is 4.61 hours every other week for the first two years of tenure before increasing with additional years of service
  • 10 paid company holidays
  • Tuition reimbursement
  • Flexible Spending Account
  • Employee Assistance Program
  • Sick time benefits – for eligible employees, one hour of sick time for every 30 hours worked, up to a maximum accrual of 40 hours per calendar year, unless the laws of the state in which the employee is located provide for more generous sick time benefits

EEO STATEMENT

Claritev is an Equal Opportunity Employer and complies with all applicable laws and regulations. Qualified applicants will receive consideration for employment without regard to age, race, color, religion, gender, sexual orientation, gender identity, national origin, disability or protected veteran status. If you would like more information on your EEO rights under the law, please click here.

APPLICATION DEADLINE

We will generally accept applications for at least 5 calendar days from the posting date or as long as the job remains posted.

#LI-MZ1

Apply now >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

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