athenahealth

athenahealth

Senior Machine Learning Engineer

Boston MA · Senior · Full-time

H1B sponsorship available$145k-$247kDetected 25 days ago
PythonSQLAWSCloud PlatformsKubernetesCI/CDLinuxMachine LearningDeep LearningSparkData EngineeringData ScienceNLPComputer VisionLLMsMLOpsStatisticsA/B TestingAgileRoadmappingCommunicationCollaborationPublic Speaking

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odds of building a lasting career here

61Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Green-card filing pattern in this occupation

Context, not a finding about this posting: of this employer's 29 green-card filings in this occupation, 100% were for a worker who already held the job.

Green-card follow-through: 96%

Of 28 labor certifications old enough to have been used, 1 expired without the employer filing the next step. Median time from filing to decision: 486 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • The individual in this role will contribute across the full machine learning lifecycle, from identifying opportunities and evaluating approaches to deploying production services and improving model performance over time.
  • This position reports to the Data Science Manager.
  • This team focuses on applying machine learning to complex healthcare problems across a variety of products and domains.

Responsibilities

  • Build scalable data pipelines, feature engineering workflows, and training datasets using structured and unstructured data.
  • Apply rigorous testing and validation methods to statistics, models, code, and production workflows to support quality and reliability.
  • Partner with platform and infrastructure teams to improve tooling for model training, deployment, observability, and reproducibility.
  • Collaborate effectively with colleagues across technical and non-technical functions to define requirements, communicate findings, and deliver solutions.
  • Our award-winning culture is built around shared values of inclusiveness, accountability, and support.

Requirements

  • Bachelor's or Master's degree in Mathematics, Computer Science, Data Science, Statistics, or a related quantitative field, or equivalent practical experience.
  • Proficiency in Python, Structured Query Language (SQL), and Unix-based development environments.
  • Experience with cloud platforms such as Amazon Web Services, including technologies such as Kubernetes, Kubeflow, or Elastic Kubernetes Service, is helpful.

Compensation

  • Expected Compensation

Benefits

  • Our company culture: Our talented employees - or athenistas, as we call ourselves - spark the innovation and passion needed to accomplish our vision.
  • We unite as mission-driven problem-solvers with a deep desire to achieve our vision and make our time here count.
  • Our DEI commitment: Our vision of accessible, high-quality, and sustainable healthcare for all requires addressing the inequities that stand in the way.
  • While we know in-office collaboration is critical to our vision, we recognize that not all work needs to be done within an office environment, full-time.
  • In addition to our traditional benefits and perks, we sponsor events throughout the year, including book clubs, external speakers, and hackathons.
  • Identify opportunities to apply machine learning techniques to healthcare product and business problems and evaluate which approaches are most appropriate.
  • Design and develop machine learning models and ML-based production services for client-facing and internal applications.
  • Deploy and maintain production machine learning services using cloud infrastructure and machine learning operations practices.
  • Support exploratory analyses, proofs of concept, and prototype development for emerging machine learning opportunities.
  • Evaluate new tools, frameworks, and methodologies relevant to machine learning engineering, data science, and generative artificial intelligence.
  • Participate in incident analysis and remediation efforts related to machine learning-enabled systems.

Company info

  • We are a diverse group of dreamers and do-ers with unique knowledge, expertise, backgrounds, and perspectives.

Visa & Work Authorization

  • In addition to our traditional benefits and perks, we sponsor events throughout the year, including book clubs, external speakers, and hackathons
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This listing is sourced directly from athenahealth's careers page and normalized into a canonical job model.