Search for Senior Machine Learning Engineer roles that are fully remote in the US, with a focus on healthcare, requiring 5+ years of experience, proficiency in Python, and familiarity with Docker.

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Senior Machine Learning Engineer

United States

Healthcare

5 years + Experience

Python

Docker

Can you help me to analyze the job description and company culture?

Sure. Here's the analysis:

Job Analysis:

The Senior Machine Learning Engineer role at SmarterDx is fundamentally designed to enhance clinical AI systems that empower hospitals to optimize patient care and revenue recovery. The successful candidate will be responsible for deploying, maintaining, and optimizing machine learning models within production environments, thereby ensuring the reliability and scalability of the solutions that healthcare providers depend on. This entails cross-functional collaboration with data scientists, data engineers, and application developers to integrate ML solutions into the broader system effectively. With the emphasis on MLOps, it's crucial that candidates are not only skilled in technical facets such as CI/CD practices and cloud technologies (AWS), but they also need to exhibit strong communication and collaboration skills. They will confront the challenge of ensuring model performance under real-world conditions, which requires an analytical mindset to improve efficiency and address any emerging issues swiftly. Success in this role will likely manifest within the first year through distinct improvements in model reliability, meaningful optimizations in model performance, and positive feedback from cross-functional teams engaged in patient care research and implementation. Lastly, familiarity with the healthcare sector, while not mandatory, would provide a strategic advantage in understanding the nuances of clinical needs and operational pain points.

Company Analysis:

SmarterDx occupies a critical niche within the healthcare technology sector, focusing on the application of AI to streamline the analysis of clinical records and enhance the value of care delivered to patients. Founded by physicians, the company blends medical insight with technological expertise to optimize revenue recovery and improve healthcare quality metrics for hospitals—essentially transforming healthcare operations. Given its relatively recent establishment in 2020, SmarterDx likely embodies an innovation-driven culture with a collaborative and fast-paced environment where agility is necessary. The company promotes a 'remote-first' strategy, indicating that it values flexibility but also anticipates candidates to be self-motivated and disciplined. This offers a unique opportunity for the Senior Machine Learning Engineer to work in a dispersed team while directly contributing to high-impact projects. The role is positioned to create long-term value for the organization, aligned with its commitment to redefining clinical decision-making through AI. Therefore, the candidate’s ability to align their technical skills with the company’s mission—improving healthcare systems—is vital for ensuring not just personal success but contributing effectively to the organization's broader objectives.

Mock up some interview questions based on the job description.

Absolutely. Here are some mock interview questions that could come up:

Tell me about a time when you had to integrate a machine learning model into an existing system. What challenges did you face, and how did you overcome them?
Describe a project where visualization or monitoring of a machine learning model's performance was key. What tools did you use?
Can you provide an example of a difficult technical problem related to MLOps that you have solved?
Tell me about a time when collaboration with a cross-functional team improved project outcomes. What did you learn from that experience?
How would you approach optimizing the performance of a machine learning model that is underperforming in production?
What steps would you take to ensure the deployment of a new model adheres to CI/CD best practices?
How would you implement monitoring to handle anomalies in model predictions once deployed in a production environment?
Imagine you are tasked with improving the scalability of our current ML solution. What strategy would you adopt?
Why are you interested in the Senior Machine Learning Engineer position at SmarterDx specifically?
What aspect of SmarterDx's mission resonates most with you, and how do you see yourself contributing to it?
Can you discuss your understanding of the healthcare sector and how it may influence your work within this role?
What is your approach to maintaining work-life balance while thriving in a remote-first work environment?
How do you stay updated with the latest advancements in machine learning and AI, and how would you apply this knowledge at SmarterDx?

Job Details

Overview Company

Senior Machine Learning Engineer

$180k/y-$230k/y

SmarterDx

8 days ago

Highlight

RemoteFull-time5+ yearsSenior

Summary

SmarterDx is seeking a Senior Software Engineer, ML Engineering to join their team remotely in the US. The role involves advancing clinical AI and supporting rapid model experimentation and development.

About the Role

As a Senior Software Engineer, ML Engineering, you will deploy and maintain machine learning models and pipelines in production environments. You will work closely with data scientists, data engineers, and application engineers to integrate ML models into the broader SmarterDx platform. Your responsibilities include crafting, implementing, and maintaining MLOps tools and practices, optimizing model performance and scalability, and contributing to the design and architecture of ML systems.

About You

Required:

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.

Preferred:

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.

Benefits

$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.

SmarterDx

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.

United States