Staff Machine Learning Engineer
4 weeks ago
Overview:
We are seeking a Staff Machine Learning Engineer/Data Scientist with 8+ years of experience to join our Bangalore team which is focused on enhancing patient care through innovative technology. Our product is a pioneering healthcare device that serves as a companion to patients, facilitating enhanced monitoring and communication with healthcare providers. The ideal candidate will possess deep expertise in Python and ML frameworks and have created data science products. This role involves leveraging advanced data science techniques to improve health outcomes by developing and managing complex data systems that include both structured and unstructured data.
Responsibilities:
- Design and implement advanced algorithms to analyze large datasets, improving and creating predictive models that enhance Aarogya Tech's health products and services.
- Manage projects from conception to final execution, integrating best practices in data governance and security.
- Operate and optimize parts of our production system.
- Utilize AWS Cloud technologies to design and manipulate heterogeneous data sets.
- Create insights from health data to enhance individual well-being.
- Design and deliver high-quality data processing solutions.
- Construct and refine data visualization dashboards.
Qualifications:
- Bachelor’s/Master's/Ph.D Degree in Computer Science or a related field.
- Minimum 8 years of experience in designing and implementing server-side data solutions, with a proven track record of delivering innovative, scalable, and impactful data science products in a competitive industry.
- Experience with health sensors/platforms for measuring physiological signals in the health, wellness and/or fitness realm
- Strong expertise in programming languages such as Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Proficiency in Python or Scala and experience with large-scale data processing using tools like Apache Spark, Hadoop, or Dask.
- Knowledge of workflow orchestrations tools such as Airflow.
- Extensive experience with AWS services and familiarity with AWS’s machine learning tools and managed services.
- Experience in data modeling, machine learning development pipelines, and creating efficient data processes.
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