Lead ML/AI Engineer

Minimum Education

• Bachelor's Degree A Bachelor's degree in a quantitative or business field (e.g., Statistics, Mathematics, Engineering, Computer Science). (Required)

Minimum Work Experience

• Requires deep functional knowledge with 10 years of related experience, or equivalent experience acquired through accomplishments of applicable knowledge, duties, scope and skill reflective of the level of this position. (Required)
  

Required Skills/Knowledge

• Experience with C# (programming language; Database Design; Java (Programming Language); JavaScript (Programming Language); Machine Leaning Machine Learning Algorithms; Python (Programming Language); R (Programming Language); Software Engineering; SWL (Programming Language); Statistics
• Experience with Continuous Integration; Predictive Modeling
• Experience with compute clouds, creating database schemas, continuous deployment
• Experience with building ML/AI models using common methods withing R and Python
• Knowledge of Open CV Linux
• Seeks to acquire knowledge in area of specialty.
• Ability to identify basic problems and procedural irregularities, collect data, establish facts, and draw valid conclusions.
• Ability to work independently.
• Demonstrated analytical skills.
• Demonstrated project management skills.
• Demonstrates a high level of accuracy, even under pressure.
• Demonstrates excellent judgment and decision-making skills.
• Ability to communicate and make recommendations to upper management.
• Ability to drive multiple projects to successful completion.
• Possesses technical aptitude.
• Excellent verbal and written communication skills, communicate complex findings in a clear and understandable manner
• Excellent facilitation ability to host sessions and elicit ideas from others, understanding their issues and encourage group participation
• Attention to detail.
• Communicate complex findings in a clear and understandable manner
• Collaborate effectively with cross-functional teams
• Adapt to changing priorities and thrive in a dynamic environment

Functional Accountabilities

• Leads the design, development, and research around complex Machine Learning (ML) systems, models, and schemes to apply to appropriate datasets for data modeling and statistical analysis

• Identifies differences and complex use cases of ML algorithms and apply findings to enable business decisions by deriving insights through data visualization

• Leads the maintenance and support of ML/AI software platforms by reviewing and solving issues and running ML/AI models

• Communicates business objectives and develops complex models that help to achieve them, along with metrics to track progress

• Leads the writing of complex software documentation and complex software code to extract data from a variety of databases and data sources

• Manages available resources such as hardware, data, and personnel so that the deadlines are met and deploy predictive models using established software patterns

• Leads the analysis of the ML algorithms that could be used to solve a given problem and rank them by their success probability.

• Explores and visualizes data to gain an understanding of it and verify data quality, and/or ensure data quality via data cleaning

• Analyses errors of the model and implements strategies to overcome errors

• Performs other duties as assigned.

• Complies with all policies and standards

Organizational Accountabilities

• Anticipate and responds to customer needs; follows up until needs are met

Teamwork/Communication

• Demonstrate collaborative and respectful behavior

• Partner with all team members to achieve goals

• Receptive to others' ideas and opinions

Performance Improvement/Problem-solving

• Contribute to a positive work environment

• Demonstrate flexibility and willingness to change

• Identify opportunities to improve clinical and administrative processes

• Make appropriate decisions, using sound judgment

Cost Management/Financial Responsibility

• Use resources efficiently

• Search for less costly ways of doing things

Safety

• Speak up when team members appear to exhibit unsafe behavior or performance

• Continuously validate and verify information needed for decision making or documentation

• Stop in the face of uncertainty and takes time to resolve the situation

• Demonstrate accurate, clear and timely verbal and written communication

• Actively promote safety for patients, families, visitors and co-workers

• Attend carefully to important details - practicing Stop, Think, Act and Review in order to self-check behavior and performance