Sr ML Operations Engineer

Employment Type: Full time

Position Overview

Interested in applying your wealth of technical knowledge and experience towards an opportunity in the medical field and improving the lives of people with diabetes? This role is responsible for building machine learning and artificial intelligence products, with a strong focus on productionizing ML and AI models. You will collaborate with data engineers, data analysts, and data scientists to solve business problems using data engineering, data science, and machine learning approaches. As a senior member of the Data Engineering & Analytics team, you will uncover customer, product, and operational insights through ML and AI product development. A passion for software engineering is highly desired to help shape the team's direction. We value self-starters, versatility, and a desire to continuously learn, improve, and empower team members. You will support building scalable, highly available, efficient, and secure software solutions for big data initiatives.

Responsibilities

• Designing, architecting, and developing machine learning and deep learning systems and platforms.
• Supporting the AI Ops needs of data science & software engineering teams across multiple products.
• Customizing large language models for product applications, with knowledge in natural language processing and generative AI.
• Leading the design and coding of big data and machine learning systems.
• Collaborating with product stakeholders to ideate and prove the viability of machine learning use cases.
• Translating business needs and goals into an AI approach and solution, and articulating findings to a non-technical audience.
• Applying advanced analytics and AI skills with a foundation in programming (e.g., R, Python), database environments (e.g., big-data platforms and SQL skills), and dashboard development.
• Designing model performance metrics, retraining schedules, and tests.
• Assisting with deploying models to cloud infrastructure such as AWS and Microsoft Azure.
• Creating software architecture and design documentation for supported solutions, and overall best practices and patterns.
• Providing architecture and technical knowledge training and support for solution groups.
• Developing good working relations with other solution teams and groups, such as Engineering, Marketing, Product, and Test/QA.
• Mentoring other engineers and data scientists, staying aware of new developments in the field, and helping to build and grow the team.

Requirements

• Bachelor's Degree in Computer Science, Information Technology, or other relevant field.
• 3 to 8 years of recent experience in ML or ML Ops in a production environment.
• Experience building end-to-end scalable ML infrastructure and data pipelines with cloud platforms.
• Strong programming (e.g., Python / Java / Kotlin) and data engineering skills.
• Experience building data pipelines for models and analytics.
• Experience with deploying and managing model endpoints.
• Experience with natural language processing and generative AI.
• Experience in time series data, signal, image, and video processing.
• Experience using the following software/tools:
  • Unsupervised, semi-supervised, and supervised learning methods.
  • Machine learning frameworks such as Keras, PyTorch, or Tensorflow.
  • Libraries such as numpy, scikit-learn, scipy, and statsmodel.
• Outstanding analytical and problem-solving skills.
• Prior experience in the healthcare or other regulated industries.
• Excellent written, verbal, and listening communication skills.
• Comfortable working asynchronously with a distributed team.
• Ability to work effectively within a team in a fast-paced, changing environment.

Company Information

• Job Family: Product Development

Application Instructions

• Application instructions were not provided in the original job description.

Salary & Location

• Salary: N/A (The base pay for this position is N/A. In specific locations, the pay range may vary from the range posted.)
• Location Type: Location type was not provided in the original job description.