Senior ML Engineer, Applied Machine Learning
Red Cell PartnersSalary not specified
- Full Time
- Senior (5 to 8 years)
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Health & Fitness, Software Development, AI & Machine LearningIndustries
Requirements
Candidates should possess at least 4 years of experience in Machine Learning, Data Science, or ML Engineering, demonstrating advanced proficiency in Python and SQL, along with strong knowledge of ML libraries such as NumPy, Pandas, and Scikit-learn. They must have solid understanding of statistical modeling, machine learning theory, and practical algorithm design, complemented by hands-on experience building, deploying, and maintaining ML models in production environments and familiarity with AWS services like SageMaker, Glue, Redshift, and Lambda. Furthermore, candidates should be proficient in ML engineering best practices including version control, CI/CD for ML, and strong communication and stakeholder management skills.
Responsibilities
The Senior Machine Learning Engineer will lead the design, development, and deployment of robust ML systems that power key business decisions, own and evolve core ML infrastructure and pipelines ensuring scalability and reliability, partner with data engineers and analysts to maintain high data quality and efficient feature pipelines, design and maintain inference APIs in production environments, build internal tools and dashboards using Streamlit to support model transparency and monitoring, track model performance and implement monitoring tools, collaborate with business stakeholders to scope ML use cases and translate them into actionable technical solutions, conduct code reviews, mentor ML Engineers and Data Scientists, and promote best practices in model development and deployment, and ensure continuous improvement of deployed models through retraining, feedback loops, and error analysis.
Skills
Python
SQL
NumPy
Pandas
Scikit-learn
Statistical modeling
Machine learning theory
Optimization
Wellth
Improves patient adherence to treatment plans
About Wellth
Wellth focuses on enhancing patient adherence to treatment plans through personalized programs based on evidence and behavioral economics. The company targets individuals who have difficulty maintaining health habits, such as taking medications or following treatment protocols, particularly in the areas of behavioral health and chronic disease management. Wellth tailors each member's experience to their specific needs, using insights from behavioral economics to tackle the reasons behind non-adherence and help members develop sustainable healthy habits. The company operates on an outcome-based payment model, meaning it only receives payment when its programs demonstrate validated success. This model appeals to healthcare providers, insurers, and employers who aim to lower healthcare costs by improving patient outcomes. Wellth's goal is to foster long-term relationships with its members while driving behaviors that positively impact healthcare costs and outcomes.
Key Metrics
Culver City, CaliforniaHeadquarters
2014Year Founded
$36.5MTotal Funding
SERIES_BCompany Stage
HealthcareIndustries
51-200Employees