Staff Software Engineer, ML Engineering

Smarter Dx, Inc; United States; Remote; USD 220,000 - 270,000; Full time

Job summary

A leading company in clinical AI is seeking a Staff Machine Learning Engineer to enhance their ML Ecosystem. This fully remote role focuses on MLOps tools, model optimization, and collaboration with data scientists to improve healthcare outcomes. Join a mission-driven team dedicated to transforming patient care through advanced AI technologies.

Benefits

Medical, Dental & Vision

One Medical Membership

Paid Parental Leave

Remote-First Team

Unlimited PTO & 10 Holidays

Learning & Development Budget

401(k) with Traditional & Roth Options

Minimal Bureaucracy

Incredible Teammates!

Qualifications

• 10+ years of development experience focused on Machine Learning and MLOps.
• Experience managing a small team using modern agile methodology.
• Strong understanding of data engineering and architecture principles.

Responsibilities

• Craft, implement, and maintain MLOps tools and practices.
• Optimize model performance and scalability.
• Build tools to improve the lives of our data scientists.

Skills

Python

SQL

Collaboration

Communication

Tools

Pytorch

Tensorflow

Docker

Kubernetes

AWS

Job description

We are looking for a Staff Machine Learning Engineer to help us build a best in class ML Ecosystem to advance our product suite with clinical AI. The ideal candidate works exceptionally well across disciplines and delivers high quality outcomes continuously, with a relentless focus on reliable systems and developer experience.

SmarterDx builds clinical AI that empowers hospitals to analyze the complete record of every patient to fully capture the value of care delivered. Founded by physicians in 2020, its proprietary AI platform understands the nuances of clinical reasoning, enabling hospitals to true the patient record for every discharge. By doing so, hospitals can recover millions in earned revenue, enhance care quality metrics, and optimize healthcare operations. Become a Smartian and help optimize the way the healthcare system works for everyone. Learn more at smarterdx.com/careers .

**This role is fully remote within the US**

What You’ll Do

• Craft, implement, and maintain MLOps tools and practices, including continuous integration, delivery, and monitoring of machine learning systems.
• Optimize model performance and scalability, ensuring high reliability and efficiency.
• Build tools to improve the lives of our data scientists.
• Contribute to the design and architecture of our ML systems.

What You Bring

10+ years of development experience with a focus on Machine Learning and MLOps roles

Strong proficiency in Python and SQL, with experience in machine learning libraries (Pytorch, Tensorflow)

Experience with deploying and managing ML models in production environments, including familiarity with Docker, Kubernetes, or similar technologies.

Understanding of CI/CD best practices for machine learning, including automated testing and deployment pipelines.

Experience with cloud platforms (preferably AWS) and their machine learning services.

Experience project managing a small team using a modern agile methodology

Experiencing influencing a cross-disciplinary organization to adopt best practices

Familiarity with infrastructure as code (e.g., CDK, Terraform) and configuration management tools.

Strong understanding of data engineering and architecture principles.

Excellent collaboration and communication skills, with a passion for solving challenging problems in a team environment.

Nice To Haves

• You're a former startup founder, or have been the first engineering hire at a startup
• Experience in the health tech domain, particularly in hospital billing systems
• Experience with end-to-end machine learning project lifecycle, from data collection and model training to deployment and monitoring.
• Deployment of LLM systems into Production environments.
• Contributions to open-source projects or active participation in the machine learning community.
• Python, PyTorch, pandas/Polars, Airflow, Snowflake, dbt, AWS, MLflow, Sagemaker, Terraform, K8s

Compensation

$220-270k base + equity incentives

• Medical, Dental & Vision– Comprehensive plans with leading insurance providers, covering 90-100% of your premiums and 70-90% for dependents, depending on the plan.
• One Medical Membership– Free membership included if you enroll in a SmarterDx medical plan.
• Paid Parental Leave– Up to 12 weeks of paid leave for birth or adoption.
• Remote-First Team– Work from anywhere in the U.S. with a $400 home office reimbursement stipend.
• Unlimited PTO & 10 Holidays– 4 of which include floating holidays so you can recognize the days that matter most to you.
• Learning & Development Budget– $500 per year (prorated) for courses, books, and resources to expand your skills.
• 401(k) with Traditional & Roth Options– Tax-advantaged retirement savings through Empower.
• Minimal Bureaucracy– A fast-moving, high-impact environment where you can focus on what matters.
• Incredible Teammates!– Work alongside smart, supportive, and mission-driven colleagues.

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Your Pronouns

Will you now or in the future require SmarterDx to file a petition or application for employment-based visa status on your behalf to begin or continue employment with our company? If you are a US citizen, your answer to this question should be "no." If you are not a US citizen and you have non-immigrant status, for example F-1 or H-1, your answer to this question should be “yes.” Please note that we regretfully cannot provide sponsorship for new employment-based visa status at this time. * Select...

This role is remote, however, you must currently reside in the United States in order to be considered. Do you currently reside in the United States? * Select...

As part of our hiring process, you will be asked to complete a background check once an offer of employment has been accepted. Are you willing to complete a background check? * Select...

Have you managed a full model implementation on the MLOps side? If so, what did that model do (can be a very broad business-based outcome goal)? *