Senior Machine Learning Engineer, Forecasting
About the role
- About Our Client:
The organization operates in the healthcare technology sector, focusing on improving surgical care through computer vision and machine learning. It develops applications that assist surgeons, nurses, and hospital administrators in delivering high-quality care by addressing critical challenges in surgical environments.
- About the Opportunity:
The Senior Machine Learning Engineer, Forecasting role is centered on building and maintaining scalable, automated machine learning pipelines and infrastructure. The position is key to enabling rapid iteration by data scientists while ensuring reliability in healthcare settings. This role contributes by productionizing ML models, automating deployment, and shaping the technical architecture of the forecasting platform to support operational efficiency and system scalability.
- Responsibilities:
Collaborate with engineering, product, and data science teams to identify opportunities for machine learning solutions
Develop tools and automate processes to enhance operational efficiency and experimentation speed
Build, integrate, and monitor large-scale distributed machine learning systems
Investigate model performance and address data quality and performance issues
Manage and improve automated model retraining and deployment pipelines for forecasting models
Advance the team''s expertise in MLOps best practices, automation, and production ML systems
- Requirements:
Over 5 years of experience with production ML systems, including MLOps, deployment automation, and model serving infrastructure
Strong software engineering skills in Python, containerization (Docker/Kubernetes), CI/CD tools (GitHub Actions, ArgoCD), and infrastructure-as-code (Terraform, Helm)
Experience with model training orchestration tools such as Dagster or Airflow and managing automated retraining pipelines
Expertise in systems design for scalable microservices, API development, and handling complex service dependencies
Proven ability to lead projects from concept to production and maintain system reliability
Effective collaboration skills with data scientists, backend engineers, and product teams
Commitment to writing tested, maintainable, and well-documented code
- Pay Range and Compensation Package:
The pay range and compensation package for this role will be determined based on the candidate’s experience, skills, and other relevant factors.
- Benefits & Perks:
Competitive salary and stock options
Flexible vacation policy
Remote-first work environment with virtual and in-person team events
Comprehensive health, dental, and vision insurance
16 weeks of parental leave for all parents
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.
Responsibilities
- Collaborate with engineering, product, and data science teams to identify opportunities for machine learning solutions
- Develop tools and automate processes to enhance operational efficiency and experimentation speed
- Build, integrate, and monitor large-scale distributed machine learning systems
- Investigate model performance and address data quality and performance issues
- Manage and improve automated model retraining and deployment pipelines for forecasting models
- Advance the team's expertise in MLOps best practices, automation, and production ML systems
Qualifications
- Over 5 years of experience with production ML systems, including MLOps, deployment automation, and model serving infrastructure
- Strong software engineering skills in Python, containerization (Docker/Kubernetes), CI/CD tools (GitHub Actions, ArgoCD), and infrastructure-as-code (Terraform, Helm)
- Experience with model training orchestration tools such as Dagster or Airflow and managing automated retraining pipelines
- Expertise in systems design for scalable microservices, API development, and handling complex service dependencies
- Proven ability to lead projects from concept to production and maintain system reliability
- Effective collaboration skills with data scientists, backend engineers, and product teams
- Commitment to writing tested, maintainable, and well-documented code
Benefits
- Competitive salary and stock options
- Flexible vacation policy
- Remote-first work environment with virtual and in-person team events
- Comprehensive health, dental, and vision insurance
- 16 weeks of parental leave for all parents
Skills mentioned
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