Senior Software Engineer, ML Engineering

Smarter Dx, Inc; United States; Remote; USD 180,000 - 230,000; Full time

Job summary

A leading company in clinical AI is seeking a Senior Machine Learning Engineer to enhance their AI platform. This fully remote role involves deploying ML models, optimizing performance, and collaborating with cross-functional teams. The ideal candidate has extensive experience in ML engineering, strong skills in Python and SQL, and familiarity with cloud platforms. Join a mission-driven team to improve healthcare outcomes.

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

• 5+ years of experience in machine learning engineering or MLOps roles.
• Experience with deploying and managing ML models in production environments.

Responsibilities

• Deploy and maintain machine learning models and pipelines in production.
• Work closely with data scientists and engineers to integrate ML models.

Skills

Python

SQL

Collaboration

Tools

PyTorch

Tensorflow

Docker

Kubernetes

AWS

Terraform

Job description

Senior Software Engineer, ML Engineering

Remote (United States)

Role

We are looking for a Senior Machine Learning Engineer to help us advance our clinical AI and support rapid model experimentation and development. The ideal candidate works exceptionally well across disciplines and delivers high quality outcomes continuously.

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

• Deploy and maintain machine learning models and pipelines in production environments.
• Work closely with data scientists, data engineers, and application engineers to integrate ML models into the broader SmarterDx platform.
• 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

• 5+ years of experience in machine learning engineering or MLOps roles
• Strong proficiency in Python and SQL, with experience in machine learning libraries (e.g. PyTorch, Tensorflow) and data manipulation (e.g., pandas, Polars, SQL).
• 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.
• 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

• 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.
• Previous work in the healthcare sector or related fields.
• Python, PyTorch, pandas/Polars, Airflow, Snowflake, dbt, AWS, MLflow, Sagemaker, Terraform, K8s

Compensation

$180-230k 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)? *