Senior Member Of Technical Staff- Machine Learning
Athenahealth1 day ago
Pune, IndiaStaff+
Responsibilities
- Identify opportunities for machine learning techniques and evaluate which approaches are most appropriate.
- Develop, evaluate, and deploy ML-based production services for healthcare clients.
- Follow and promote best practices for modeling, coding, architecture, and statistics.
- Apply rigorous testing to statistical methods, models, and code.
- Contribute to internal data science tools, standards, and team practices.
- Collaborate with product, engineering, platform, and technical and non-technical colleagues in small scrum teams.
Requirements
- Bachelor’s or master’s degree in mathematics, computer science, data science, statistics, or a related field.
- 3–5 years of professional hands-on experience developing, evaluating, and deploying machine learning models.
- Experience with Python, SQL, and Unix.
- Strong communication and writing skills.
- Preferred experience with deep learning models and complex neural network architectures.
- Preferred experience training and fine-tuning LLMs and GenAI models.
- Familiarity with natural language processing or computer vision techniques.
- AWS ecosystem experience, including Kubernetes, Kubeflow, or EKS, is preferred.
Benefits
- Health and financial benefits.
- Location-specific commuter support, employee assistance programs, tuition assistance, employee resource groups, and collaborative workspaces.
- Flexible work arrangements balancing in-office collaboration with digital collaboration tools.
- Company-sponsored events including book clubs, external speakers, and hackathons.
- Learning support, an engaged team, and an inclusive work environment.
Tech Stack
Categories
About Athenahealth
Athenahealth builds cloud-based electronic health records, practice management, revenue cycle, and patient engagement software for medical practices and health systems, often paired with technology-enabled billing services. The company sells its platform on a subscription basis and supports high-volume clinical and financial workflows across its network. Founded in 1997 and headquartered in Boston, it is privately held under Bain Capital.