The Senior Machine Learning Engineer will lead AI initiatives, develop ML infrastructure, establish data engineering best practices, and collaborate across teams to enhance healthcare technology services.
Accompany Health is on a mission to give patients with complex needs the dignified, high-quality care they deserve but rarely receive. A primary, behavioral, and social care provider, Accompany Health walks alongside patients for their entire care journey, offering at-home and virtual care, as well as 24/7 support. Partnering with innovative payors, Accompany Health is powered by remarkable care teams, elegant technology, and a commitment to evidence-based practice.
We build long-term relationships with our patients so they know, without question, that our team is here for them day or night, year after year. We focus on the health outcomes most important to our patients to make it clear that they lead the way.
To achieve our mission, we collaborate with community-based organizations, local providers, and health plans. Led by our empathetic care teams, guided by proven care models, and powered by our own technology, we deliver a level of service that our communities rightfully deserve but rarely receive.
While our headquarters is in Bethesda, MD, our teams are distributed across the country. If you’re eager to make a tangible difference in people’s lives, to help correct long-standing disparities in health care, join us.
About the role:
As a Senior Machine Learning Engineer for Accompany Health, you will help us transform healthcare through AI.
-Mission-critical, be part of our growing team (and company).
-Collaborate across the organization with various teams, including Product, Sales, and Clinical Operations, to rewire health care: Your choices will matter, and you will work across multiple teams to help execute the choices.
-Drive the change in healthcare: You will build the products to integrate highly fragmented and dispersed healthcare services as an end-to-end experience.
-Be part of building a great engineering culture, maintaining the balance and right tradeoff for building products for speed and tech debt.
Responsibilities will include:
- Technical Leadership
- Drive AI initiatives and collaborate with teams to leverage data effectively through model development and evaluation.
- Design and implement scalable Machine Learning infrastructure and solutions, ensuring reliability and performance.
- Help establish data engineering best practices and promote standards that enhance data accessibility across teams.
- Data Strategy & Architecture
- Create and maintain optimal AI pipeline architecture with high observability and robust operational characteristics.
- Champion responsible AI development by implementing and reviewing models that maximize data value while ensuring fairness and equity.
- Assemble large, complex data sets that address functional and strategic requirements.
- Collaboration & Enablement
- Partner with other teams such as; Executive, Product, Clinical, Data, and Design
- Identify, design, and implement process improvements to enhance efficiency and scalability.
- Create tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Quality & Innovation
- Develop efficient, reliable AI pipelines with strong monitoring and observability.
- Navigate and optimize our data ecosystem to drive meaningful insights.
- Design and implement comprehensive evaluation frameworks and benchmarks to rigorously assess model performance, accuracy and reliability.
Desired skills and experience:
- Required:
- 5+ years of software engineering experience, with a focus on building production-grade machine learning systems, backend infrastructure, or MLOps.
- Graduate degree in Computer Science, Statistics, or related quantitative field.
- Strong proficiency in Python and SQL, with the ability to create efficient and maintainable code for machine learning applications.
- Developing and maintaining ML pipelines for model training, evaluation, deployment (experience with tools like AWS Sagemaker or Bedrock is preferred).Healthcare experience is valuable but not required.
- Developing and implementing modern LLM models and transformers and deploying ML models in a production environment. Designing and implementing best practices for model versioning, experimentation, and reproducibility.
- Continuously improving our ML infrastructure for stability, scalability, observability, and security.
- Developing internal tooling and libraries to enhance ML workflow efficiency.
You Have Hands-on experience in:
What makes you a fit for the team: Your entrepreneurial mindset and ability to articulate complex technical ideas will be essential as you collaborate across our remote team to solve novel problems at the intersection of AI and compassionate care delivery.
Decision making authority: Exercises moderate to high authority for standard decisions and limited to moderate authority for non-standard decisions that impact others.
#LI-Remote
#LI-LP1
For Patient Facing Roles
To keep our patients, communities and each other safe, you'll be required to comply with Accompany Health’s medical clearance requirements, including completing a TB screen and providing proof of immunity or vaccination for certain conditions. This is a condition of employment, and we make exceptions as required by law. Accommodation for religious and medical beliefs will be provided on a case by case basis.
We embrace diversity and believe it creates a healthier atmosphere: Accompany Health is an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status, sexual orientation, gender identity or expression, marital status, genetic information, or any other characteristic protected by law.
Top Skills
Aws Sagemaker
Bedrock
Python
SQL
Similar Jobs
eCommerce • Healthtech • Kids + Family • Retail • Social Media
Lead the development of ML solutions to enhance user experience at Babylist. Build recommender systems and personalization features from scratch, collaborating with a cross-functional team.
Top Skills:
AirflowAWSMySQLPandasPythonPyTorchReactRedisRuby On RailsSklearnXgboost
.png)
Artificial Intelligence • Blockchain • Fintech • Financial Services • Cryptocurrency • NFT • Web3
As a Senior Machine Learning Engineer at Coinbase, you will lead the design, development, and deployment of advanced risk detection models while mentoring junior engineers. You'll collaborate on technical roadmaps and apply cutting-edge ML methodologies to enhance security against fraud and scams.
Top Skills:
Apache AirflowGnnsKafkaLlmsLstmsPythonPyTorchSparkTensorFlow
Artificial Intelligence • Blockchain • Fintech • Financial Services • Cryptocurrency • NFT • Web3
The Senior Machine Learning Engineer will design, build, and lead strategies for risk detection models, mentor team members, and apply advanced AI/ML methodologies to enhance user security and experience.
Top Skills:
Ai/Ml FrameworksApache AirflowFeature StoresGnnsKafkaLlmsLstmsPythonPyTorchRayserveSparkTensorFlow
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
