Machine Learning Engineer II/III (Applied Research & Model Development)

• About Our Client
• The organization operates in the field of AI-powered pathology, using machine learning and artificial intelligence to improve patient outcomes through more accurate diagnoses and more effective disease treatment, particularly in cancer care. Its technology has been deployed across translational research, pathology laboratories, and clinical trials. The organization brings together a diverse team of scientists, engineers, and medical experts focused on solving complex healthcare challenges through rigorous scientific analysis.
• About the Opportunity
• The Machine Learning Engineer II/III (Applied Research & Model Development) develops and deploys machine learning models that advance medical research and patient care. The role collaborates across scientific, engineering, and product teams to translate biological and clinical needs into scalable ML solutions. Depending on level, the position ranges from contributing to projects under guidance to leading initiatives, setting technical direction, and mentoring team members.
• Responsibilities
• • Design, develop, and deploy machine learning models for research and product development.
• • Collaborate with scientists, engineers, and product teams to translate biological and clinical requirements into ML solutions.
• • Participate in experimental design, documentation, analysis, and interpretation of results.
• • Contribute to knowledge sharing through design reviews, technical discussions, and ML best practices.
• • Improve machine learning pipelines and infrastructure in partnership with MLOps and platform teams.
• • Publish and present scientific work through abstracts, manuscripts, conferences, and other technical forums.
• • For MLE II, contribute to projects under guidance, implement ML models, and develop expertise in established engineering and research practices.
• • For MLE III, lead projects from concept through deployment, establish technical direction, mentor team members, and identify new research and product opportunities.
• Requirements
• • MLE II: Master’s degree with 2–4 years of relevant experience or Ph.D. with 0–2 years of relevant experience.
• • MLE III: Master’s degree with 5+ years of relevant experience or Ph.D. with 3+ years of relevant experience.
• • Proven experience developing and deploying machine learning models in production or research environments.
• • Proficiency in Python, machine learning frameworks, and data pipeline development.
• • Ability to work independently while collaborating effectively across multidisciplinary teams.
• • Strong written and verbal communication skills.
• • MLE III: Deep expertise in machine learning, computer vision, biomedical AI, or a related field, with significant technical contributions.
• • Advanced proficiency in ML frameworks, software engineering, and model deployment pipelines.
• • Leadership experience, including project management and mentoring.
• • Ability to communicate how technical contributions translate into business, research, or clinical impact.
• • Record of scientific contributions through publications, presentations, or comparable work.
• Pay Range and Compensation Package
• • Machine Learning Engineer II: $107,250–$164,450 annual salary range.
• • Machine Learning Engineer III: $130,500–$200,100 annual salary range.
• • These positions are not eligible for overtime compensation.

Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin.

Note:

RemoteHunter is not the Employer of Record (EOR) for this role. Our purpose in this opportunity is to connect exceptional candidates with leading employers. We help job seekers worldwide discover roles that match their goals and guide them to complete their full application directly through the hiring company’s career page or ATS.