Machine Learning Engineer

The Opportunity:
Our Data Science team provides technical leadership, direction, and implementation services for the consumption of data by Enterprise Analytics platforms. We partner with our clients and are primarily responsible for leading and engaging in transformation and modernization initiatives. This is a hands-on practice with the expectation of actively participating in implementing the solutions.

Requirements:

1. Partner with our clients to build end-to-end Data Consumption Platforms leveraging your unique Business and Technical skills to perform exploratory data analysis, build and validate models, and deploy models into established pipelines.
2. Deliver AI/ML solutions, providing thought leadership, use-case ideation and development, Pipeline establishment, and AI/MLOps capabilities.
3. Ideate and build state-of-the-art data ecosystems that drive valuable insights for clients across Healthcare, Life Sciences, Financial Services, etc.
4. Validate technical approaches to ensure consistency with business direction and desired functionality.
5. This requires hands-on experience/projects involving real-world analytical problems using machine learning and a solid understanding of statistical methods and modeling.
6. Experience in AI/ML algorithm development and data analysis (NLP, time-series analysis, computer vision, etc.).
7. Experience in traditional ML and deep learning techniques, AI optimization, and deployment of data science applications.
8. Experience with tools, languages, and data science packages like Python, R, Keras, Tensorflow, PyTorch, Pandas, Scikit-learn, Jupyter, etc.
9. Experience with Image and Text Recognition and Computer Vision applications.
10. Experience in cloud-based data science ecosystems such as AWS, Azure, or GCP for development and deployment of models along with corresponding native data science tools like AWS SageMaker, Azure ML Studio to build and scale ML pipelines.
11. Collaborate with data engineers, data scientists, project managers, and business teams to ensure delivery and presentations are aligned with business objectives.
12. Experience with the software release cycle, productionizing ML or predictive analytics models at scale.

Benefits:

• Rapid Career Acceleration
• One-to-One Projects, Community Outreach
• Diverse & Inclusive Working Environment
• Paid Time Off
• 401k
• Medical, Dental, Vision
• Remote work