Senior Machine Learning Engineer
Remote
Full Time Senior-level / Expert USD 135K - 180K
Nomad Health
Join thousands of clinicians nationwide to find your next travel nurse or allied health job with Nomad Health.Position Summary
As a Senior Machine Learning Engineer, you will own the delivery of high-impact machine learning projects end-to-end. Your goal will be to utilize Nomad’s extensive historical data and state-of-the-art machine learning algorithms and approaches to deliver effective models that change the game for Nomad.
Responsibilities/What You Will Do
The MLE role overlaps with many disciplines, such as Operations, Data Science, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:
- Fully own the process of designing, building, and/or delivering ML models and components that solve critical business problems.
- Creatively solve challenging problems by building application code using machine learning approaches and technologies.
- Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of algorithm, training data, engineered features, model training, hyperparameter tuning, dimensionality, bias/variance, and validation.
- Retrain, maintain, and monitor models in production.
- Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
- Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
- Utilize Jira to document, organize, and communicate your workflows to the team and stakeholders.
- Utilize best practices for code collaboration (git).
Qualifications/ Skills - What You Will Need
- Competency
- Python (OOP)
- SQL/BigQuery
- Broad Machine Learning Knowledge and expertise in at least one area of Machine Learning (NLP, recommendations, predictive modeling, NNs, image processing)
- Cloud Services (AWS or GCP)
- Git best practices
- (preferred) Experience deploying ML models in a production environment
- (preferred) Experience working with an ML platform like ML Flow or Databricks
- Required education and experience - 4+ years experience developing real-world ML applications in a professional setting.
- Additional eligibility qualifications - Master’s Degree or equivalent work experience preferred.
Don’t meet every single requirement? We encourage you to apply - you may be just the right candidate for this or other roles at Nomad Health. Studies show that individuals from marginalized communities are less likely to apply for jobs unless they meet every requirement. Nomad Health is dedicated to a diverse, inclusive, and authentic culture.
The Company has reviewed this job description to ensure that essential functions and basic duties have been included. It is intended to provide guidelines for job expectations and the employee's ability to perform the position described. It is not intended to be construed as an exhaustive list of all functions, responsibilities, skills, and abilities. Additional functions and requirements may be assigned by supervisors as deemed appropriate. This document does not represent a contract of employment, and the Company reserves the right to change this position description and/or assign tasks for the employee to perform, as the Company may deem appropriate.
Nomad Health is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. All employment is decided on the basis of qualifications, merit, and business need.
Compensation for this full-time position is between $135,000 to $180,000. This range reflects the minimum and maximum amount employees can earn during their time in the role. Actual pay may be higher or lower depending on geographic locations, skills, experience, and other factors permitted by law.
Tags: Architecture AWS BigQuery Databricks Engineering GCP Git Jira Machine Learning ML infrastructure ML models Model training MongoDB NLP OOP Predictive modeling Python SQL
Perks/benefits: Startup environment Team events
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