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Medical Machine Learning Jobs in Georgia (NOW HIRING)

Based on eligibility, role and job status, we offer many programs including medical, dental, vision ... Terracon's internship program gives students the opportunity to turn classroom learning into ...

Complete familiarity with various statistical and machine learning techniquesincluding ... An aptitudefor medical informatics is preferred WHAT YOU'LL NEED Additional * Worksclosely ...

Complete familiarity with various statistical and machine learning techniquesincluding ... An aptitudefor medical informatics is preferred WHAT YOU'LL NEED Additional * Worksclosely ...

Machine Operator

Willacoochee, GA ยท On-site

$13.75 - $16.25/hr

You are energized when learning about new products and machinery. ARE power tools and machine ... Medical with 100% preventative care coverage * Health Savings Account * Dental and Vision * 401K

Machine Operator

Willacoochee, GA

$13.75 - $16.25/hr

You are energized when learning about new products and machinery. ARE power tools and machine ... Medical with 100% preventative care coverage * Health Savings Account * Dental and Vision * 401K

... implementing machine learning and analytical systems applied to design information and user ... medical informatics Company : Waystar is a technology platform that provides healthcare revenue ...

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Medical Machine Learning information

See Georgia salary details

$30.8K

$139.1K

$284.6K

How much do medical machine learning jobs pay per year?

As of Jul 12, 2026, the average yearly pay for medical machine learning in Georgia is $139,096.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,000.00 and $226,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Medical Machine Learning position, and why are they important?

To thrive in Medical Machine Learning, you need a strong background in computer science, statistics, and biomedical sciences, often supported by an advanced degree in a related field. Familiarity with programming languages (such as Python or R), machine learning frameworks (like TensorFlow or PyTorch), and healthcare data management systems is crucial. Strong problem-solving abilities, collaboration skills, and the ability to communicate complex technical concepts to a diverse audience make a candidate stand out. These skills are critical for developing robust, effective machine learning solutions that can impact patient care and integrate seamlessly into clinical workflows.

What is a Medical Machine Learning job?

A Medical Machine Learning job involves developing and applying AI algorithms to analyze medical data, such as imaging, electronic health records, and genomics, to improve diagnosis, treatment, and patient outcomes. Professionals in this field work with clinicians, data scientists, and engineers to create predictive models, automate medical workflows, and ensure compliance with healthcare regulations. Strong knowledge of machine learning, data processing, and healthcare-specific challenges is essential.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer or AI research director, often found in tech companies or healthcare organizations. These roles usually require advanced skills in machine learning, deep learning, and data analysis, along with extensive experience and sometimes specialized certifications. Compensation at this level reflects leadership responsibilities, expertise, and the impact of AI solutions in the organization.

Is ML a high paying job?

Medical machine learning professionals typically earn high salaries due to the specialized skills required, such as expertise in data analysis, programming, and healthcare knowledge. Salaries can vary based on experience, education, location, and industry demand, but overall, it is considered a well-compensated field within tech and healthcare sectors.

Will MLE be replaced by AI?

Medical Machine Learning Engineers (MLEs) develop and implement algorithms to analyze medical data, and AI advancements are augmenting their work rather than replacing it. While AI tools automate certain tasks, MLEs are essential for designing, validating, and maintaining complex models within healthcare environments, often requiring domain expertise and programming skills. The role is expected to evolve with AI, emphasizing collaboration between human expertise and automated systems.

What does machine learning do in healthcare?

In healthcare, machine learning is used by professionals to analyze large datasets, improve diagnostic accuracy, and develop predictive models for patient outcomes. Medical machine learning specialists often work with algorithms, programming tools, and clinical data to enhance treatment plans and healthcare efficiency.

What types of teams do Medical Machine Learning professionals typically collaborate with in a healthcare setting?

Medical Machine Learning professionals often work in multidisciplinary teams that include data scientists, clinicians, software engineers, and regulatory experts. Collaboration with healthcare providers is common to ensure models address real clinical needs and comply with healthcare standards. You'll typically interact closely with IT departments for data access and security, as well as with research teams and sometimes external partners. Working in such dynamic teams allows you to contribute technical expertise while gaining insights from domain experts, leading to more successful and impactful machine learning projects.

What are the most commonly searched types of Medical Machine Learning jobs in Georgia? The most popular types of Medical Machine Learning jobs in Georgia are:
Vice President, Data & AI Strategy (Fully Remote)

Vice President, Data & AI Strategy (Fully Remote)

PadSplit

Atlanta, GA โ€ข Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 27 days ago


Job description

The Role We Need

PadSplit is looking for a Vice President, Data & AI Strategy to transform data, machine learning, and artificial intelligence into a strategic advantage that improves outcomes for our members, hosts, and business. Reporting directly to the CTO, this leader will oversee our Analytics, Machine Learning, and AI functions while driving responsible AI adoption across the company. This role will ensure our data and AI investments generate measurable business impact while maintaining the trust and ethical standards our mission demands.

The Person We Are Looking For

We are looking for an experienced executive who has successfully led integrated data, analytics, and machine learning organizations and has personally driven AI adoption at scale. The ideal candidate combines strong technical judgment with business acumen, helping leaders separate meaningful opportunities from hype while translating complex concepts into action. They are a pragmatic, mission-driven leader who can influence executives, develop teams, and ensure data and AI are deployed responsibly to improve people's lives.

Here's What You'll Be Doing Day-to-Day:
  • AI Strategy Leadership: Define and execute PadSplit's company-wide AI strategy, including adoption goals, governance standards, enablement programs, and business impact measurement.
  • Organization Leadership: Lead the Analytics, Business Intelligence, Machine Learning, and AI enablement teams as a unified data and AI organization.
  • Roadmap Ownership: Drive the machine learning and predictive analytics roadmap, including pricing optimization, risk modeling, search relevance, and future AI-powered capabilities.
  • Data Platform Management: Oversee the health, quality, governance, scalability, and cost efficiency of PadSplit's data ecosystem.
  • Responsible AI Governance: Partner with Legal and executive stakeholders to establish ethical AI standards and responsible deployment practices.
  • Product Partnership: Collaborate with Product teams to build data-driven experiences and predictive features that improve member and host outcomes.
  • Executive Decision Support: Translate data and analytics into actionable insights that influence decisions across Product, Finance, Marketing, and Operations.
  • Technology Evaluation: Assess emerging AI and machine learning technologies and determine where they can create meaningful business value.
Here's What You'll Need to Be Successful:
  • Executive Leadership: 10+ years of experience in data, analytics, machine learning, or AI leadership roles, including experience managing managers.
  • Integrated Team Leadership: Proven success leading both analytics and machine learning functions within a single organization.
  • AI Deployment Experience: Demonstrated track record implementing AI solutions at scale and measuring business outcomes.
  • Technical Expertise: Strong understanding of modern data platforms, machine learning systems, analytics tooling, and AI technologies such as Snowflake, dbt, and Hex.
  • Ethical AI Perspective: Clear point of view on AI governance, responsible deployment, bias mitigation, and customer impact.
  • Executive Communication: Ability to influence senior leaders, present to boards, challenge assumptions, and simplify complex technical concepts.
  • Cross-Functional Partnership: Experience working across Product, Finance, Marketing, Legal, and Operations to deliver business outcomes through data.
  • Data Platform Stewardship: Hands-on familiarity with modern data stacks and experience managing data quality, governance, and platform costs.
The Interview Process:
  • Your application will be reviewed for possible next steps by the Hiring Manager.
  • If you meet eligibility requirements, the next step would be a phone call with a member of the PeopleOps team for about thirty (30) minutes.
  • If warranted, the next step would be a video interview with our CTO for one (1) hour.
  • If warranted, the next step would be a video panel interview with members of our leadership team for one (1) hour.
  • If warranted, the next step would be a video panel interview with key stakeholders at PadSplit for two (2) hours.
  • The panel interview will require a candidate to work on a data assessment where you will showcase your data and AI skills to the panel for discussion.ย 
  • If warranted, the final interview would be with our CEO.
  • If warranted, then we move to offer!
Compensation, Benefits, and Perks:
  • Fully remote position - we swear!
  • Competitive compensation package including an equity incentive plan and company-wide bonus opportunity
  • National medical, dental, and vision healthcare plans
  • Company provided life insurance policy
  • Optional accidental insurances, FSA, and DCFSA benefits
  • Unlimited paid-time (PTO) policy with eleven (11) company-observed holidays
  • 401(k) planย 
  • Twelve (12) weeks of paid time off for both birth and non-birth parents
  • The opportunity to do what you love at a company that is at the forefront of solving the affordable housing crisis
$0 - $0 a year
Compensation is based on the role's scope, national market benchmarks, the person's expertise and experience, and the impact of their contributions to our business goals.
Please note:ย Although the job posting says it's in Atlanta, Georgia, this is a fully remote position. This is a result of our Applicant Tracking System requiring a location to post the role on LinkedIn.
ย 
Notice to Applicants:
ย 
PadSplit participates in E-Verify. All new employees are required to complete an I-9 form and be authorized to work in the United States. Employment is contingent upon successful completion of the E-Verify process.
ย 
PadSplit is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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