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$166K–$240K is typical
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USA - Remote
Live, first seen by us 67 days agoExperience Level: 10+ yrs Work Location: USA - Remote Role Overview:
Listed location: USA - RemoteRead the full posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
As an ATA Machine Learning Engineer in healthcare, you'll deliver multi-geography projects, empowering healthcare organizations with data ingestion, cloud services, and DevOps.
Build and scale GenAI and LLM models into cloud-based healthcare SaaS production
Design healthcare use cases such as predictive models, summarization, and semantic search
Develop high-level solution architectures with offshore engineers and analysts
Ensure responsible AI through quality, fairness, and safety checks
Lead architecture discussions with clients and mentor senior resources
As an ATA Machine Learning Engineer in healthcare, you'll deliver multi-geography projects, empowering healthcare organizations with data ingestion, cloud services, and DevOps. You'll collaborate with Cloud, Software, and Data Engineering teams to build platforms and solutions for digital diagnosis, software as a medical product, and AI marketplaces.
Apply GenAI and LLM-based ML/AI techniques to develop, scale, and integrate model systems and solutions into large-scale cloud-based SaaS production environments for healthcare
Design, build, and evaluate solutions for healthcare use cases (e.g., predictive models, summarization, semantic search)
Develop high-level solution architectures, collaborating with offshore big-data engineers and decision science analysts
Ensure responsible AI practices, including quality, fairness, and safety
Lead technical discussions on architecture design and troubleshooting with clients, proactively providing solutions, and mentor senior resources/team leads
Hands-on experience working with healthcare data (e.g. EHR, ADT, clinical notes).
Ability to lead technology teams and provide them mentorship / support to accelerate performance.
Hands-on experience with statistical tools and techniques
Ability to mentor and groom junior members of the team and provide them with guidance and roadmap.
Proficiency in Python. Proficiency in Java or other languages is helpful.
Ability to handle conflicts effectively by managing internal and external stakeholders
Must have: - Ph.D grad, with 1+ years related industry experience OR Masters grad with 4+ years industry experience--including at least 1 year directly related to healthcare ML/AI - Proven industry experience through multiple major product releases in a commercial SaaS environment.
As an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS, and Snowflake, we build and deliver enterprise-grade AI services and solutions that create real-world impact.
In the employer’s words · Read in context
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$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
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- Hands-on experience working with healthcare data (e.g. EHR, ADT, clinical notes). - Proficiency in Python. Proficiency in Java or other languages is helpful. - Proficiency with SQL and data engineering for AI/ML applications.
- Proficiency in Python. Proficiency in Java or other languages is helpful. - Proficiency with SQL and data engineering for AI/ML applications. - Experience working with large datasets using big data frameworks (e.g. Azure Data Lake, Apache Spark or Databricks)
Since our founding in 2013, Quantiphi has tackled some of the world’s most complex business challenges by combining deep industry expertise, disciplined cloud and data engineering practices, and cutting-edge applied AI research. Our work is rooted in delivering accelerated, quantifiable business value, not just technology for technology’s sake. Headquartered in Boston, Quantiphi is a global organization with 4,000+ professionals serving clients across key industry verticals, including BFSI, Healthcare & Life Sciences, CPG, MFG, TME etc. As an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS, and Snowflake, we build and deliver enterprise-grade AI services and solutions that create real-world impact. We’ve been recognized with:
- 17x Google Cloud Partner of the Year awards in the last 8 years. - 3x AWS AI/ML award wins. - 3x NVIDIA Partner of the Year titles.
- Experience building and evaluating models using modern ML packages such as NumPy, SciPy, Pandas, Scikit-learn, PyTorch, and LightGBM. - Experience building and deploying models using public cloud infrastructure (Azure, AWS, or Google Cloud), including familiarity with version control, CI/CD pipelines, and scaling considerations for production ML systems at SaaS scale. - Strong communication and collaboration skills; comfortable working on a distributed team.
- Proficiency with SQL and data engineering for AI/ML applications. - Experience working with large datasets using big data frameworks (e.g. Azure Data Lake, Apache Spark or Databricks) - Solid understanding of transformer models and LLM-based approaches, including hands-on experience with prompt tuning and PEFT methods (e.g. LoRA, QLoRA) using frameworks such as Hugging Face Transformers.
- 3x NVIDIA Partner of the Year titles. - 2x Snowflake Partner of the Year awards. - We have also garnered top analyst recognitions from Gartner, ISG, and Everest Group.
- Experience working with large datasets using big data frameworks (e.g. Azure Data Lake, Apache Spark or Databricks) - Solid understanding of transformer models and LLM-based approaches, including hands-on experience with prompt tuning and PEFT methods (e.g. LoRA, QLoRA) using frameworks such as Hugging Face Transformers. - Experience building and evaluating models using modern ML packages such as NumPy, SciPy, Pandas, Scikit-learn, PyTorch, and LightGBM.
- Solid understanding of transformer models and LLM-based approaches, including hands-on experience with prompt tuning and PEFT methods (e.g. LoRA, QLoRA) using frameworks such as Hugging Face Transformers. - Experience building and evaluating models using modern ML packages such as NumPy, SciPy, Pandas, Scikit-learn, PyTorch, and LightGBM. - Experience building and deploying models using public cloud infrastructure (Azure, AWS, or Google Cloud), including familiarity with version control, CI/CD pipelines, and scaling considerations for production ML systems at SaaS scale.
We’ve been recognized with: - 17x Google Cloud Partner of the Year awards in the last 8 years. - 3x AWS AI/ML award wins.
Complete your application on quantiphi.wd1.myworkdayjobs.com. The employer’s form will show what is required.
Already applied? Track this application
Yes. We’ve followed one other Architect ML - AI Researcher job there since June 2026. It came down after 79 days.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
About Quantiphi:
Quantiphi is an award-winning, AI-First digital engineering and consulting company focused on delivering high-impact Services and Solutions that help organizations solve what truly matters. We partner with enterprises to reimagine their businesses through intelligent, scalable, and transformative AI driving measurable outcomes at the very core of their operations.
Since our founding in 2013, Quantiphi has tackled some of the world’s most complex business challenges by combining deep industry expertise, disciplined cloud and data engineering practices, and cutting-edge applied AI research. Our work is rooted in delivering accelerated, quantifiable business value, not just technology for technology’s sake.
Headquartered in Boston, Quantiphi is a global organization with 4,000+ professionals serving clients across key industry verticals, including BFSI, Healthcare & Life Sciences, CPG, MFG, TME etc. As an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS, and Snowflake, we build and deliver enterprise-grade AI services and solutions that create real-world impact.
We’ve been recognized with:
17x Google Cloud Partner of the Year awards in the last 8 years.
3x AWS AI/ML award wins.
3x NVIDIA Partner of the Year titles.
2x Snowflake Partner of the Year awards.
We have also garnered top analyst recognitions from Gartner, ISG, and Everest Group.
We offer first-in-class industry solutions across Healthcare, Financial Services, Consumer Goods, Manufacturing, and more, powered by cutting-edge Generative AI and Agentic AI accelerators.
We have been certified as a Great Place to Work for the third year in a row- 2021, 2022, 2023.
Be part of a trailblazing team that’s shaping the future of AI, ML, and cloud innovation.
Your next big opportunity starts here!
For more details, visit: Website or LinkedIn Page.
Role: Architect Machine Learning
Experience Level: 10+ yrs
Work Location: USA - Remote
Role Overview:
As an ATA Machine Learning Engineer in healthcare, you'll deliver multi-geography projects, empowering healthcare organizations with data ingestion, cloud services, and DevOps. You'll collaborate with Cloud, Software, and Data Engineering teams to build platforms and solutions for digital diagnosis, software as a medical product, and AI marketplaces.
Key Responsibilities:
Apply GenAI and LLM-based ML/AI techniques to develop, scale, and integrate model systems and solutions into large-scale cloud-based SaaS production environments for healthcare.
Design, build, and evaluate solutions for healthcare use cases (e.g., predictive models, summarization, semantic search), performing research, experimentation, data management, and model evaluation.
Develop high-level solution architectures, collaborating with offshore big-data engineers and decision science analysts to build, test, and assess models predicting and optimizing client business outcomes.
Ensure responsible AI practices, including quality, fairness, and safety, using frameworks like LLM-as-judge, RAGAS, and LangSmith.
Translate complex insights into simple, quantifiable business impacts for clients, cultivating deep relationships by understanding their needs.
Lead technical discussions on architecture design and troubleshooting with clients, proactively providing solutions, and mentor senior resources/team leads.
Collaborate across functions (product, clinical, data science, engineering) and with offshore delivery managers to ensure seamless communication and delivery.
Contribute to a collaborative team culture, sharing knowledge, and identifying sales opportunities.
Basic Qualifications:
Must have:
Ph.D grad, with 1+ years related industry experience OR Masters grad with 4+ years industry experience--including at least 1 year directly related to healthcare ML/AI
Proven industry experience through multiple major product releases in a commercial SaaS environment.
Hands-on experience working with healthcare data (e.g. EHR, ADT, clinical notes).
Proficiency in Python. Proficiency in Java or other languages is helpful.
Proficiency with SQL and data engineering for AI/ML applications.
Experience working with large datasets using big data frameworks (e.g. Azure Data Lake, Apache Spark or Databricks)
Solid understanding of transformer models and LLM-based approaches, including hands-on experience with prompt tuning and PEFT methods (e.g. LoRA, QLoRA) using frameworks such as Hugging Face Transformers.
Experience building and evaluating models using modern ML packages such as NumPy, SciPy, Pandas, Scikit-learn, PyTorch, and LightGBM.
Experience building and deploying models using public cloud infrastructure (Azure, AWS, or Google Cloud), including familiarity with version control, CI/CD pipelines, and scaling considerations for production ML systems at SaaS scale.
Strong communication and collaboration skills; comfortable working on a distributed team.
Experience with one or more of: reinforcement learning or RLHF, NLP techniques for summarization, extraction, classification, or semantic search, retrieval-augmented generation (RAG) pipelines and/or agentic frameworks (e.g. LangChain, LlamaIndex).
Leadership qualities
Provide thought leadership to the team and bring industry best practices to the project.
Ability to lead technology teams and provide them mentorship / support to accelerate performance.
Ability to handle conflicts effectively by managing internal and external stakeholders
Experience in leading multiple large projects as well as a deep understanding of Agile developments
Effective communication with all the stakeholders involved.
communicate clearly about complex subjects and technical plans with technical and non technical audiences.
Good to have:
Hands-on experience with statistical tools and techniques
Experience with Agile/Scrum/DevOps software development methodologies.
Critical eye for the quality of data and strong desire to get it right.
Other Qualifications (OQs):
Effective communication with all the stakeholders involved
Need to communicate clearly about complex subjects and technical plans
Ability to mentor and groom junior members of the team and provide them with guidance and roadmap.
Must also have the ability to interact with other members of the team (Juniors, Seniors, ATA, TA, BA, etc) to get their designs from concept to development
Keeping various audiences in mind, engineers must write their reports in clear language accessible to all.
What’s in it for YOU at Quantiphi:
Make an impact at one of the world’s fastest-growing AI-first digital engineering companies.
Upskill and discover your potential as you solve complex challenges in cutting-edge areas of technology alongside passionate, talented colleagues.
Work where innovation happens - work with disruptive innovators in a research-focused organization with 60+ patents filed across various disciplines.
Stay ahead of the curve—immerse yourself in breakthrough AI, ML, data, and cloud technologies and gain exposure working with Fortune 500 companies.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
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USA - Remote
Experience Level: 10+ yrs Work Location: USA - Remote Role Overview:
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