Senior Member of Technical Staff- Machine Learning
Athenahealth16 hours ago
Bengaluru, IndiaSenior / Staff+
Responsibilities
- Identify opportunities for different machine learning techniques and evaluate which approaches are most suitable.
- Develop, evaluate, and help deploy ML-based production services for healthcare clients.
- Follow and promote best practices for modeling, coding, architecture, and statistics.
- Apply rigorous testing to statistics, machine learning models, and code.
- Contribute to internal tools and data science team standards while collaborating in small scrum teams.
Requirements
- Bachelor’s or master’s degree in mathematics, computer science, data science, statistics, or a related field.
- 5–8 years of professional hands-on experience developing, evaluating, and deploying machine learning models.
- Experience with Python, SQL, and Unix.
- Strong communication and writing skills, including the ability to work with technical and non-technical colleagues.
- Deep learning experience with complex neural network architectures is a bonus.
- Experience training and fine-tuning LLM and GenAI models is a bonus.
- Familiarity with natural language processing or computer vision techniques.
- AWS ecosystem experience, including Kubernetes, Kubeflow, or EKS, is a bonus.
Benefits
- Health and financial benefits, with location-specific perks such as commuter support, employee assistance programs, tuition assistance, employee resource groups, and collaborative workspaces.
- Flexible work arrangements that support a balance between in-office collaboration and work outside the office.
- Company-sponsored events including book clubs, external speakers, and hackathons.
- Learning opportunities, 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.