Machine Learning Engineer

Reposted 18 Days Ago
Be an Early Applicant
Hiring Remotely in Bom Pastor, Minas Gerais
In-Office or Remote
190K-210K Annually
Senior level
Artificial Intelligence • Healthtech • Software
The Role
The Machine Learning Engineer collaborates to design, deploy, and maintain ML models for medical imaging, ensuring production readiness and optimization.
Summary Generated by Built In

Company Description:

At HOPPR, we empower developers to build the next generation of AI medical imaging applications, with the goal of making clinical care and workflow optimization more accessible, efficient, and equitable within the healthcare systems they serve.

Role Description:

The Machine Learning Engineer will collaborate with researchers, engineers, and clinicians to design and deploy scalable machine learning solutions, building shared ML infrastructure and optimizing models for production. This role requires a blend of technical expertise, problem-solving skills, and the ability to integrate machine learning solutions into enterprise-grade products, driving innovations that improve patient care.

Key Responsibilities:

  • Develop, deploy, and maintain state-of-the-art machine learning models for medical imaging, NLP, and multimodal tasks. 
  • Design and implement robust, scalable ML pipelines and shared infrastructure to support agile experimentation and deployment. 
  • Collaborate with researchers to translate novel algorithms into production-ready solutions. 
  • Build and maintain MLOps tools and practices, including automated testing, continuous integration, and monitoring of deployed models. 
  • Optimize model performance for speed, reliability, and scalability in production environments. 
  • Partner with clinicians, engineers, and product teams to align machine learning efforts with clinical and product needs. 

Minimum Qualifications (Knowledge, Skills, and Abilities)

  • Bachelor’s degree in Computer Science, Engineering, or a related field with 5+ years' experience in relevant roles.
  • Proficiency in Python and machine learning frameworks such as PyTorch or TensorFlow.
  • Strong understanding of MLOps practices, including model deployment, CI/CD pipelines, and performance monitoring.
  • Experience working with cloud platforms (e.g., AWS, GCP, Azure) and tools like Docker and Terraform.
  • Familiarity with healthcare data and clinical workflows is a plus.
  • Exceptional problem-solving skills, ownership mindset, and a collaborative approach.
  • Thrive in a dynamic and rewarding environment that emphasizes excellence, autonomy, and impact. 

Essential Job Functions

HOPPR is committed to providing reasonable accommodation to employees with disabilities, as required by law. We encourage those with disabilities to request accommodations if needed to perform the essential functions of the job.

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

  • While performing the duties of this job, the employee may be regularly required to stand, sit, talk, hear, reach, stoop, kneel, and use hands and fingers to operate a computer, telephone, and keyboard.
  • Specific vision abilities required by this job include close vision requirements due to computer work.
  • Regular, predictable attendance is required; including quarter-driven hours as business demands dictate.
  • Some travel may be required.

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

  • Ability to sit at a computer terminal for an extended period.
  • Moderate noise (i.e., phone calls, online meetings, computer audio).

Why Join Us:

  • Innovation: Be a part of a pioneering company at the forefront of generative AI in healthcare, contributing to revolutionary advancements in medical imaging.
  • Impact: Play a critical role in transforming radiology and medical imaging through cutting-edge technology, directly impacting patient care and outcomes.
  • Growth: Enjoy opportunities for professional development and career advancement in a rapidly growing industry.
  • Culture: Join a dynamic and supportive team that values innovation, collaboration, and excellence.

 What We Offer:

  • Competitive salary and benefits package.
  • Opportunity to work with a leading company in AI in medical imaging.
  • Flexible working hours and fully remote position, some travel is required.
  • Collaborative and innovative work environment.
  • Health insurance and retirement plans programs.
  • Professional development opportunities and support for continuous learning.

HOPPR is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Important Note: This opportunity is open exclusively to US citizens and permanent residents. We kindly request that recruiters and agencies refrain from contacting Dr. Khan Siddiqui or any HOPPR team members directly regarding this role. Unrequested outreach from recruiters will not be entertained or responded to. Thank you for respecting this directive and helping us maintain a focused and efficient hiring process.

Remote - USA
$190,000$210,000 USD

Top Skills

AWS
Azure
Docker
GCP
Python
PyTorch
TensorFlow
Terraform
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The Company
HQ: Chicago, IL
49 Employees
Year Founded: 2019

What We Do

HOPPR is building the first multimodal AI foundation model for medical imaging - founded by Khan Siddiqui, (CEO - founder of higi) and Oliver Chen (COO - founder of ilumihealth, acquired by Fosun Pharma) to accelerate AI application development and fine-tuning of AI models. Its deep learning platform is based on a proprietary privacy-compliant trust architecture that brings together data sources and AI/ML developers.

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