Know ATS Score
CV/Résumé Score
  • Expertini Resume Scoring: Our Semantic Matching Algorithm evaluates your CV/Résumé before you apply for this job role: Machine Learning Engineer I Multimodal Artificial Intelligence for Women's Health (On Site).
United States Jobs Expertini

Urgent! Machine Learning Engineer I - Multimodal Artificial Intelligence for Women's Health (On Site) Job Opening In NEW YORK – Now Hiring Mount Sinai Health System

Machine Learning Engineer I Multimodal Artificial Intelligence for Women's Health (On Site)



Job description

**Job Description**

Machine Learning Engineer I will be primarily responsible for contributing to the development and enhancement of machine learning applications and systems.

They will work closely with other engineers and data scientists to design and implement scalable and efficient machine learning systems.

We are recruiting a Machine Learning Engineer I to support the lab’s core projects in multimodal AI for women’s health.

The engineer will be responsible for building, optimizing, and deploying ML pipelines at scale, working with both postdocs and clinicians.

This role is ideal for an applied researcher who is excited about translational machine learning and thrives in a collaborative, interdisciplinary environment.

Heavy menstrual bleeding affects nearly one in three women of reproductive age and is a leading cause of iron deficiency worldwide.

Yet it remains one of the most under-recognized challenges in medicine.

Our lab at the intersection between the Artificial Intelligence and Human Health Department and the Department for Obstetrics, Gynecology and Reproductive Sciences at Mount Sinai has been awarded a Wellcome Leap _Missed Vital Sign_ grant to change this.

We are building a new, interdisciplinary group at the intersection of AI, human health, and obstetrics & gynecology.

Our mission is to harness state-of-the-art methods in machine learning and multimodal data integration to close critical gaps in women’s health—and to translate these advances into solutions that matter for patients and clinicians.

As a founding member, you will help shape a lab designed for openness, collaboration, and translation.

You will have access to unique resources including Mount Sinai’s genome-linked EHR biobank (the Sinai Million), AIRMS (AI-ready Mount Sinai Integrated Data and Analytics Platform), the Minerva HPC cluster, and eHive, a digital platform for wearable and real-world data collection.

Partnerships with the Hasso Plattner Institute in Germany create further opportunities for international collaboration.

This is a chance to join at the ground level of a lab committed to impact: bringing computational innovation directly into women’s health.

**Qualifications**

**Requirements**

+ Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, Biomedical Informatics or related field.
+ Experience in applied machine learning and deep learning using PyTorch
+ Experience in HPC environments, distributed training, and large scale data processing
+ Familiarity with version control, containerization (Docker, Singularity) and reproducible research practices
+ Experience with clinical data and biomedical informatics (OMOP, FHIR) preferred
+ Background in multi-modal Machine Learning, time series analysis, or computer vision preferred
+ Azure Cloud experience preferred
+ Interest in translational applications in Women's Health preferred
+ Knowledge of at least one programming language among Scala, Python, Java, C, or C++.
+ Knowledge of big data technologies (e.g., Hadoop, Spark)
+ Knowledge of Software Development Lifecycle.
+ Self-motivated with a demonstrated ability to work independently, and to exercise independent judgment in developing complex techniques or programs in a dynamic environment.
+ Act as the major contributor in the development and operationalization of four different applications.
+ Play a key technical role in maintaining deployed products
+ Understanding of machine learning algorithms (Supervised, Unsupervised ML algorithms).
+ Familiarity with SQL or other database languages.

**Responsibilities**

+ Build, train and evaluate machine learning models on large scale multimodal datasets (wearables, imaging, genomics, EHR)
+ Develop and maintain reproductible, scalable ML pipelines using PyTorch
+ Run experiments on HPC clusters (Minerva) and support distributed learning (e.g. Accelerate, Lightning)
+ Optimize workflows for compute and data efficiency
+ Collaborate with post-doctoral fellows and clinical researchers to translate models into practice
+ Contribute to codebases, documentation and open source tools
+ Assist in the collection, cleaning, and curation of large data sets.
+ Assist in the operationalization of machine learning models.
+ Participate in evaluating model performance and contribute to model refinement.
+ Work with other team members to deploy machine learning models.
+ Contribute to maintaining clear and organized documentation of machine learning systems.
+ Stay updated with the latest trends and technologies in the machine learning field.
+ Work collaboratively with a multidisciplinary team to ensure the effectiveness of machine learning systems.
+ Develop and maintain project work plans, including critical tasks, milestones, timelines, interdependencies, and contingencies.

Tracks and reports progress.

Keeps stakeholders apprised of project status and implications for completion.
+ Prepare clear, well-organized project-specific documentation, including, at a minimum, analytic methods used, key decision points and caveats, with sufficient detail to support comprehension and replication.
+ Share development and process knowledge with other analysts in order to assure redundancy and continuously builds a core of analytical strength within the organization.
+ Adhere to corporate standards for performance metrics, data collection, data integrity, query design, and reporting format to ensure high quality, meaningful analytic output.
+ Works closely with IT on the ongoing improvement of Mount Sinai’s integrated data warehouse, driven by strategic and business needs, and designed to ensure data and reporting consistency throughout the organization.
+ Demonstrates advanced level proficiency with the principles and methodologies of process improvement.

Applies these in the execution of responsibilities in support of a process focused approach.
+ Other duties as assigned.

**About Us**

**Strength through Unity and Inclusion**

The Mount Sinai Health System is committed to fostering an environment where everyone can contribute to excellence.

We share a common dedication to delivering outstanding patient care.

When you join us, you become part of Mount Sinai’s unparalleled legacy of achievement, education, and innovation as we work together to transform healthcare.

We encourage all team members to actively participate in creating a culture that ensures fair access to opportunities, promotes inclusive practices, and supports the success of every individual.

At Mount Sinai, our leaders are committed to fostering a workplace where all employees feel valued, respected, and empowered to grow.

We strive to create an environment where collaboration, fairness, and continuous learning drive positive change, improving the well-being of our staff, patients, and organization.

Our leaders are expected to challenge outdated practices, promote a culture of respect, and work toward meaningful improvements that enhance patient care and workplace experiences.

We are dedicated to building a supportive and welcoming environment where everyone has the opportunity to thrive and advance professionally.

Explore this opportunity and be part of the next chapter in our history.

**About the Mount Sinai Health System:**

Mount Sinai Health System is one of the largest academic medical systems in the New York metro area, with more than 48,000 employees working across eight hospitals, more than 400 outpatient practices, more than 300 labs, a school of nursing, and a leading school of medicine and graduate education.

Mount Sinai advances health for all people, everywhere, by taking on the most complex health care challenges of our time — discovering and applying new scientific learning and knowledge; developing safer, more effective treatments; educating the next generation of medical leaders and innovators; and supporting local communities by delivering high-quality care to all who need it.

Through the integration of its hospitals, labs, and schools, Mount Sinai offers comprehensive health care solutions from birth through geriatrics, leveraging innovative approaches such as artificial intelligence and informatics while keeping patients’ medical and emotional needs at the center of all treatment.

The Health System includes more than 9,000 primary and specialty care physicians; 13 joint-venture outpatient surgery centers throughout the five boroughs of New York City, Westchester, Long Island, and Florida; and more than 30 affiliated community health centers.

We are consistently ranked by U.S. News & World Report's Best Hospitals, receiving high Honor Roll status, and are highly ranked: No. 1 in Geriatrics, top 5 in Cardiology/Heart Surgery, and top 20 in Diabetes/Endocrinology, Gastroenterology/GI Surgery, Neurology/Neurosurgery, Orthopedics, Pulmonology/Lung Surgery, Rehabilitation, and Urology.

New York Eye and Ear Infirmary of Mount Sinai is ranked No. 12 in Ophthalmology.

U.S. News & World Report’s “Best Children’s Hospitals” ranks Mount Sinai Kravis Children's Hospital among the country’s best in several pediatric specialties.

The Icahn School of Medicine at Mount Sinai is ranked No. 11 nationwide in National Institutes of Health funding and in the 99th percentile in research dollars per investigator according to the Association of American Medical Colleges.

Newsweek’s “The World’s Best Smart Hospitals” ranks The Mount Sinai Hospital as No. 1 in New York and in the top five globally, and Mount Sinai Morningside in the top 20 globally.

**Equal Opportunity Employer**

The Mount Sinai Health System is an equal opportunity employer, complying with all applicable federal civil rights laws.

We do not discriminate, exclude, or treat individuals differently based on race, color, national origin, age, religion, disability, sex, sexual orientation, gender, veteran status, or any other characteristic protected by law.

We are deeply committed to fostering an environment where all faculty, staff, students, trainees, patients, visitors, and the communities we serve feel respected and supported.

Our goal is to create a healthcare and learning institution that actively works to remove barriers, address challenges, and promote fairness in all aspects of our organization.

**Compensation Statement**
Mount Sinai Health System (MSHS) provides a salary range to comply with the New York City Law on Salary Transparency in Job Advertisements.

The salary range for the role is $109000 - $163695 Annually.

Actual salaries depend on a variety of factors, including experience, education, and hospital need.

The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.



Required Skill Profession

Other General



Your Complete Job Search Toolkit

✨ Smart • Intelligent • Private • Secure

Start Using Our Tools

Join thousands of professionals who've advanced their careers with our platform

Rate or Report This Job
If you feel this job is inaccurate or spam kindly report to us using below form.
Please Note: This is NOT a job application form.


    Unlock Your Machine Learning Potential: Insight & Career Growth Guide


  • Real-time Machine Learning Jobs Trends in NEW YORK, United States (Graphical Representation)

    Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph below. This graph displays the job market trends for Machine Learning in NEW YORK, United States using a bar chart to represent the number of jobs available and a trend line to illustrate the trend over time. Specifically, the graph shows 10816 jobs in United States and 367 jobs in NEW YORK. This comprehensive analysis highlights market share and opportunities for professionals in Machine Learning roles. These dynamic trends provide a better understanding of the job market landscape in these regions.

  • Are You Looking for Machine Learning Engineer I Multimodal Artificial Intelligence for Women's Health (On Site) Job?

    Great news! is currently hiring and seeking a Machine Learning Engineer I Multimodal Artificial Intelligence for Women's Health (On Site) to join their team. Feel free to download the job details.

    Wait no longer! Are you also interested in exploring similar jobs? Search now: .

  • The Work Culture

    An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Mount Sinai Health System adheres to the cultural norms as outlined by Expertini.

    The fundamental ethical values are:
    • 1. Independence
    • 2. Loyalty
    • 3. Impartiality
    • 4. Integrity
    • 5. Accountability
    • 6. Respect for human rights
    • 7. Obeying United States laws and regulations
  • What Is the Average Salary Range for Machine Learning Engineer I Multimodal Artificial Intelligence for Women's Health (On Site) Positions?

    The average salary range for a varies, but the pay scale is rated "Standard" in NEW YORK. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

  • What Are the Key Qualifications for Machine Learning Engineer I Multimodal Artificial Intelligence for Women's Health (On Site)?

    Key qualifications for Machine Learning Engineer I Multimodal Artificial Intelligence for Women's Health (On Site) typically include Other General and a list of qualifications and expertise as mentioned in the job specification. Be sure to check the specific job listing for detailed requirements and qualifications.

  • How Can I Improve My Chances of Getting Hired for Machine Learning Engineer I Multimodal Artificial Intelligence for Women's Health (On Site)?

    To improve your chances of getting hired for Machine Learning Engineer I Multimodal Artificial Intelligence for Women's Health (On Site), consider enhancing your skills. Check your CV/Résumé Score with our free Tool. We have an in-built Resume Scoring tool that gives you the matching score for each job based on your CV/Résumé once it is uploaded. This can help you align your CV/Résumé according to the job requirements and enhance your skills if needed.

  • Interview Tips for Machine Learning Engineer I Multimodal Artificial Intelligence for Women's Health (On Site) Job Success
    Mount Sinai Health System interview tips for Machine Learning Engineer I   Multimodal Artificial Intelligence for Women's Health (On Site)

    Here are some tips to help you prepare for and ace your job interview:

    Before the Interview:
    • Research: Learn about the Mount Sinai Health System's mission, values, products, and the specific job requirements and get further information about
    • Other Openings
    • Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.
    • Dress Professionally: Choose attire appropriate for the company culture.
    • Prepare Questions: Show your interest by having thoughtful questions for the interviewer.
    • Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.
    During the Interview:
    • Be Punctual: Arrive on time to demonstrate professionalism and respect.
    • Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.
    • Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.
    • Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.
    • Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.
    • Follow Up: Send a thank-you email to the interviewer within 24 hours.
    Additional Tips:
    • Be Yourself: Let your personality shine through while maintaining professionalism.
    • Be Honest: Don't exaggerate your skills or experience.
    • Be Positive: Focus on your strengths and accomplishments.
    • Body Language: Maintain good posture, avoid fidgeting, and make eye contact.
    • Turn Off Phone: Avoid distractions during the interview.
    Final Thought:

    To prepare for your Machine Learning Engineer I Multimodal Artificial Intelligence for Women's Health (On Site) interview at Mount Sinai Health System, research the company, understand the job requirements, and practice common interview questions.

    Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Mount Sinai Health System's products or services and be prepared to discuss how you can contribute to their success.

    By following these tips, you can increase your chances of making a positive impression and landing the job!

  • How to Set Up Job Alerts for Machine Learning Engineer I Multimodal Artificial Intelligence for Women's Health (On Site) Positions

    Setting up job alerts for Machine Learning Engineer I Multimodal Artificial Intelligence for Women's Health (On Site) is easy with United States Jobs Expertini. Simply visit our job alerts page here, enter your preferred job title and location, and choose how often you want to receive notifications. You'll get the latest job openings sent directly to your email for FREE!