Senior Member Of Technical Staff- Machine Learning 

Join us as we work to create a thriving ecosystem that delivers accessible,
high-quality, and sustainable healthcare for all. Position Summary: Join
athenahealth as a Senior Machine Learning Engineer on the Data Science team
within the Clinicals division. In this in-person role based in Bangalore, India,
you will design, build, and deploy machine learning and deep learning solutions
that improve clinical and operational outcomes for healthcare providers. You
will partner with product, clinical, data, and engineering teams to move models
from research into production and help ensure they are reliable, measurable, and
maintainable. This role reports to the Senior Engineering Manager. About the
Team: The Data Science team develops machine learning solutions for healthcare
products and workflows. The team works with product managers, clinicians, and
engineers to turn clinical and operational problems into measurable machine
learning use cases. Work spans the full model lifecycle, including exploratory
analysis, feature engineering, model development, evaluation, reproducibility,
automated training pipelines, and monitored production deployment. The team uses
a range of methods, including supervised learning, deep learning, and generative
AI, to support use cases such as document understanding, clinical natural
language processing, and workflow improvement. The team also partners closely
with platform engineers to deploy models using cloud technologies and production
orchestration so that machine learning is scalable, observable, and maintainable
across the product portfolio. Essential Job Responsibilities: Develop
production-ready machine learning and deep learning models using Python and
related libraries. Implement and evaluate neural network architectures for
natural language processing and computer vision use cases in healthcare. Design
and build data pipelines and feature engineering workflows. Integrate models
into scalable production environments using containerization and orchestration
patterns. Optimize model performance, conduct error analysis, and design
validation and monitoring processes. Collaborate with product managers,
clinicians, and engineers to translate clinical problems into measurable machine
learning solutions and acceptance criteria. Evaluate deep learning frameworks,
transformer-based models, and foundation model approaches, including large
language models and generative AI, to solve product problems. Apply prompt
design and testing practices to improve generative AI outputs and align them
with product requirements. Use AI tools in development and analysis workflows to
speed experimentation, compare model outputs, and review results, while
validating findings before they are used in production decisions. Additional Job
Responsibilities: Research and prototype model architectures or training
strategies relevant to product goals. Support model fine-tuning and transfer
learning workflows for domain-specific large language models. Contribute to
internal tooling and shared libraries for reproducible training and evaluation.
Participate in design reviews, code reviews, and cross-team technical
discussions. Help define data collection and labeling priorities with product
and annotation partners. Contribute to documentation for model governance,
reproducibility, and on-call support. Mentor junior engineers and support
knowledge sharing within the team. Assist with performance tuning and cost
optimization for training and inference workloads. Participate in security and
privacy reviews related to model data and deployment. Contribute to discussions
on machine learning safety, fairness, and responsible AI practices. Expected
Education & Experience: Bachelor’s or Master’s degree in Computer Science,
Electrical Engineering, Statistics, Mathematics, or a related field, or
equivalent practical experience. 5–8 years of hands-on experience building and
deploying machine learning or deep learning models in production. Proficiency in
Python, SQL, and Unix/Linux environments. Experience developing and implementing
deep learning models with complex neural network architectures. Familiarity with
deep learning frameworks such as PyTorch or TensorFlow, transformer models, and
NLP or computer vision libraries. Experience with large language models,
generative AI techniques, prompt design, and model fine-tuning. Familiarity with
NLP or computer vision techniques and evaluation metrics. Experience with cloud
environments and infrastructure is preferred; familiarity with AWS, Kubernetes,
Kubeflow, or EKS is a plus. About athenahealth Our vision: In an industry that
becomes more complex by the day, we stand for simplicity. We offer IT solutions
and expert services that eliminate the daily hurdles preventing healthcare
providers from focusing entirely on their patients — powered by our vision to
create a thriving ecosystem that delivers accessible, high-quality, and
sustainable healthcare for all. Our company culture: Our talented  employees —
or athenistas, as we call ourselves — spark the innovation and passion needed to
accomplish our vision. We are a diverse group of dreamers and do-ers with unique
knowledge, expertise, backgrounds, and perspectives. We unite as mission-driven
problem-solvers with a deep desire to achieve our vision and make our time here
count. Our award-winning culture is built around shared values of inclusiveness,
accountability, and support. Our DEI commitment: Our vision of accessible,
high-quality, and sustainable healthcare for all requires addressing the
inequities that stand in the way. That's one reason we prioritize diversity,
equity, and inclusion in every aspect of our business, from attracting and
sustaining a diverse workforce to maintaining an inclusive environment for
athenistas, our partners, customers and the communities where we work and serve.
What we can do for you: Along with health and financial benefits, athenistas
enjoy perks specific to each location, including commuter support, employee
assistance programs, tuition assistance, employee resource groups, and
collaborative  workspaces  — some offices even welcome dogs. We also encourage a
better work-life balance for athenistas with our flexibility. 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. With consistent
communication and digital collaboration tools, athenahealth enables employees to
find a balance that feels fulfilling and productive for each individual
situation. In addition to our traditional benefits and perks, we sponsor events
throughout the year, including book clubs, external speakers, and hackathons. We
provide athenistas with a company culture based on learning, the support of an
engaged team, and an inclusive environment where all employees are valued. Learn
more about our culture and benefits here: athenahealth.com/careers
https://www.athenahealth.com/careers/equal-opportunity United by our mission and
driven by our entrepreneurial spirit, our work at athenahealth is collaborative,
transformative, and above all, it’s meaningful. Our employees take pride in
using technology and data-driven insights to inspire changes that will make the
U.S. healthcare system better for everyone, including your friends, family and
maybe even you. Notice to Job Seekers/Job Candidates: Recruitment Fraud Alert
Please be aware of questionable job offers that are not affiliated with
athenahealth. athenahealth has been made aware of unauthorized career
opportunities offered by individuals posing as representatives of larger U.S.
companies, including athenahealth. The fictitious jobs are advertised on
employment-search websites, such as Indeed.com and Craigslist.com, and
prospective employees are required to share their personal and financial
information (e.g. credit card, bank information), provide copies of their
government-issued identification, and/or send money for application fees,
processing charges or work permits. The victims who are told they are "hired"
are often instructed to deposit a check (which is later returned as fraudulent)
into their own account and to forward overpayment to individuals - usually via
wire transfer. Important information for job seekers: athenahealth has a formal
application process and we do not request you to interview on a Google Hangout
or via text messaging. athenahealth will never request money for the opportunity
to apply or work for athenahealth. athenathealth does not require completion of
tax forms, bank account or credit card information as part of the recruiting
process. If you feel that you have been a victim of such a scam, please send an
email to: askhr@athenahealth.com