Pay
$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.
Pleasanton, CA, United States
Open 4 months, first seen by us 124 days agoWork setup in the employer’s posting: RemoteFrom the employer’s posting
Employment type in the employer’s posting: InternFrom the employer’s posting
Join Sajix as a Machine Learning Engineer Trainee to assist in building and deploying ML models that enhance our healthcare intelligence platform and improve clinical outcomes.
Support training and deployment of machine learning models
Implement algorithms in production with data scientists
Learn model optimization, testing, and monitoring
Solve classification and prediction problems on real healthcare datasets
Join Sajix as a Machine Learning Engineer Trainee to assist in building and deploying ML models that enhance our healthcare intelligence platform and improve clinical outcomes.
Support training and deployment of machine learning models.
Collaborate with data scientists to implement algorithms in production.
Learn about model optimization, testing, and monitoring.
Work on real-world healthcare datasets to solve classification and prediction problems.
Bachelor’s/Master’s in Computer Science, Data Science, or related field.
Solid programming skills in Python.
Understanding of ML algorithms and frameworks like TensorFlow, PyTorch, or Scikit-learn.
Bonus: Exposure to model deployment tools or cloud platforms.
Requirements: - Bachelor’s/Master’s in Computer Science, Data Science, or related field. - Solid programming skills in Python.
Open 4 monthsWe first saw this posting 124 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$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.
Day 124
Up longer than most. Similar jobs usually come down between day 6 and day 69.
From 4,331 similar postings that came down. Coming down is not always a hire.
4 open jobs
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- Bachelor’s/Master’s in Computer Science, Data Science, or related field. - Solid programming skills in Python. - Understanding of ML algorithms and frameworks like TensorFlow, PyTorch, or Scikit-learn.
- Solid programming skills in Python. - Understanding of ML algorithms and frameworks like TensorFlow, PyTorch, or Scikit-learn. - Bonus: Exposure to model deployment tools or cloud platforms.
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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.
About the Role:
Join Sajix as a Machine Learning Engineer Trainee to assist in building and deploying ML models that enhance our healthcare intelligence platform and improve clinical outcomes.
Key Responsibilities:
Support training and deployment of machine learning models.
Collaborate with data scientists to implement algorithms in production.
Learn about model optimization, testing, and monitoring.
Work on real-world healthcare datasets to solve classification and prediction problems.
Requirements:
Bachelor’s/Master’s in Computer Science, Data Science, or related field.
Solid programming skills in Python.
Understanding of ML algorithms and frameworks like TensorFlow, PyTorch, or Scikit-learn.
Bonus: Exposure to model deployment tools or cloud platforms.
These trainee roles are offered in collaboration with Sajix’s __init__py program—a structured, hands-on learning initiative aimed at nurturing the next generation of full-stack developers and technology professionals. The program offers tiered training tracks.
Participants gain real-world experience through live projects, personalized mentorship, and exposure to industry-relevant tools and practices. This collaboration ensures that trainees are well-equipped with practical skills and knowledge to excel in their roles.
For more information about the __init__py program, visit initpy.sajix.com.
Sajix Inc. is a global health-tech company headquartered in Pleasanton, California, focused on transforming healthcare delivery through advanced digital solutions. Since its founding in 2006, Sajix has specialized in developing integrated healthcare information systems that streamline clinical, financial, and administrative operations for healthcare organizations around the world.
With operations in the United States, United Kingdom, Singapore, and India, Sajix serves clients across North America, Europe, Asia, and Africa. Its flagship platform, iHelix, is a modular, scalable solution designed for use in diverse healthcare settings—from single-doctor practices to large hospital networks.
Sajix offers a comprehensive suite of digital healthcare solutions, including:
iHelix
Lifeeazy
AI-based Revenue Cycle Management – optimizing financial workflows through automation
All products are built with global standards in mind, supporting multiple languages and currencies, and comply with international healthcare regulations such as CCR and CCD.
Through strategic partnerships and a commitment to innovation, Sajix continues to lead the industry in delivering intelligent, interoperable, and patient-centric healthcare solutions.
Website: www.sajix.com
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Pleasanton, CA, United States
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