Join us as we work to create a thriving ecosystem that delivers accessible, high-quality, and sustainable healthcare for all. Machine Learning Engineer — Senior Member of Technical Staff (Senior Associate) Role summary: You will design, build, and deploy advanced machine learning and deep learning solutions that improve clinical and operational outcomes for healthcare providers. This in-person role is based in Pune, India and requires 3–5 years of relevant experience. The successful candidate will collaborate closely with product, data, and platform engineering teams to move models from research to production and will report to the Senior Engineering Manager. Team summary: We are looking for a Senior Machine Learning Engineer to join the Data Science team within the Athena Clinicals Division. You will work with the team to develop and deploy machine learning models across a variety of healthcare products and domains. The data science team is bringing machine learning to bear against the hardest problems in healthcare. We partner with product managers, clinicians, and engineering teams to translate clinical and operational problems into measurable ML use cases. Our work spans the full model lifecycle: exploratory analysis, feature engineering, model development, rigorous evaluation, reproducibility, automated training pipelines, and monitored production deployments. The team applies a range of methods — from traditional supervised learning to modern deep learning and generative AI — to solve problems such as document understanding, clinical NLP, clinician workflows, etc. We place a strong emphasis on model safety, explainability, and measurable impact on care delivery and practice operations. The team works hand-in-hand with platform engineers to deploy state-of-the-art models using cloud technologies and production orchestration (CI/CD, containerization, orchestration), and we aim to make ML deliverable, observable, and maintainable at scale across athenahealth’s product portfolio. About you: You enjoy owning end-to-end technical work and solving challenging problems. You keep up with advances in machine learning, especially deep learning and generative AI, and apply them thoughtfully to real-world product needs. You have hands-on experience building, evaluating, and deploying ML and deep learning models, and are comfortable communicating results and trade-offs to technical and non-technical stakeholders. You write clean, well-documented code, and collaborate effectively with cross-functional teams to produce reliable, auditable solutions. You are motivated by improving healthcare outcomes using data and models. Essential Job Responsibilities: •Develop production-ready machine learning and deep learning models using Python and relevant libraries. •Implement and evaluate complex neural network architectures (NLP and/or computer vision) for healthcare use cases. •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 rigorous validation and monitoring processes. •Collaborate with product managers, clinicians, and engineers to translate clinical problems into measurable ML solutions and acceptance criteria. •Evaluate and adopt deep learning frameworks, transformer-based models, and foundational model techniques (LLMs/GenAI) to solve product problems. •Apply prompt engineering and optimization practices to improve generative AI outputs and alignment with product requirements. •AI competency expectation: Integrate AI and generative-model capabilities into development workflows—evaluate new AI tools and model variants for product fit, prototype responsible uses, and recommend best practices for safe, reliable deployment of AI features that enhance clinical and operational decision-making. •Communicate technical trade-offs, design decisions, and model limitations clearly in writing and presentations. Additional Job Responsibilities: •Research and prototype novel model architectures or training strategies relevant to product goals. •Support model fine-tuning and transfer learning workflows for domain-specific LLM 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 in partnership with product and annotation teams. •Contribute to documentation for model governance, reproducibility, and runbooks for on-call support. •Mentor junior engineers and contribute to knowledge sharing within the team. •Assist in performance tuning and cost optimization for training and inference workloads. •Participate in security and privacy reviews related to model data and deployment. •Attend and contribute to community discussions on ML 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). •3–5 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 libraries for NLP/vision. •Experience with LLMs, generative AI techniques, and prompt engineering; training and fine-tuning LLMs. •Familiarity with NLP or computer vision techniques and evaluation metrics. •Experience with cloud environments and infrastructure is a must ; Hands on working knowledge of AWS, Kubernetes, Docker, Harness, EKS is a must •Strong verbal and written communication skills for cross-functional collaboration and stakeholder-facing documentation. 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

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