Principal AI Engineer

Description

This is a remote role, so you will mainly work from home.

The company connects, protects, analyzes and acts on customer data and applications across edge and cloud environments.

This senior-level AI engineer role builds integrated algorithms that structure and analyze structured and unstructured data in products and systems, using large-scale computing frameworks, data analysis systems and modeling environments.

You will apply machine learning and statistical models to improve product and system performance, data management, quality and accuracy. You will build descriptive, diagnostic, predictive and prescriptive algorithms, turn technical specifications into code, and apply deep learning so systems can perceive, learn from and respond to complex situations.

You will turn customer needs and industry trends into AI and ML products, solutions and improvements, with a visible technical impact on a product or major subcomponent. Priorities include faster time-to-market, lower costs and meeting current and future customer needs.

You will be a recognized internal authority in your technical area, leading technical work on significant projects, taking part in cross-functional initiatives and sharing knowledge through mentoring.

Job level: TCP05.

Responsibilities

• Design, build and deploy advanced machine learning models and algorithms, including choosing techniques, preparing data, engineering features, training and evaluating.
• Lead research into new approaches by running experiments, testing new algorithms and finding chances to innovate, while keeping up with the field.
• Architect AI systems for scalability, performance and reliability by tuning algorithms and using distributed computing frameworks and cloud services.
• Work with data scientists, software engineers and product managers to clarify requirements, identify where AI fits, and guide development with technical advice.
• Mentor junior engineers in AI and machine learning practice, reviewing their work and giving feedback to build their skills.
• Lead design reviews across several projects to keep design choices consistent and standards high, and act as a key mentor to the team.
• With the engineering manager and team lead, set long-term design and implementation direction.
• Build feedback loops and continuous improvement into the development process.
• Lead team meetings to track progress, resolve issues and coordinate work, and help the engineering manager set agendas.
• Prepare high-level reports and presentations for executives, explaining complex technical strategy and its impact on business goals.
• Use data mining, data modeling, natural language processing and machine learning to extract and analyze information from datasets.
• Where relevant, help design and develop solutions to complex application, system administration or network problems.

Requirements

• Bachelor's or master's degree in computer science, engineering, data science, machine learning, artificial intelligence or a closely related quantitative field.
• 8+ years of experience in AI and machine learning.
• Solid understanding of AI and ML fundamentals, including supervised and unsupervised learning, deep learning, reinforcement learning, natural language processing, computer vision and statistical modeling.
• Hands-on experience implementing and deploying machine learning algorithms such as decision trees, random forests, support vector machines and neural networks. Knowledge of TensorFlow, PyTorch or sci-kit is required.
• Strong programming in Python, Java or C++ is required, with the ability to write clean, efficient, maintainable code and apply software engineering best practices.
• Skill in preparing and cleaning data, including wrangling, feature extraction, dimensionality reduction, handling missing values and fixing data quality issues.
• Solid linear algebra, calculus, probability and statistics, which are crucial for designing and evaluating models.
• Data visualization skills to analyze and present insights to technical and non-technical stakeholders.
• Strong communication skills to work across teams, explain complex AI concepts to non-technical stakeholders, and mentor junior engineers.
• Experience leading research, publishing papers or contributing to open-source AI projects.
• Experience guiding and mentoring other engineers.
• Continuous learning and a drive for innovation are essential.
• Deep learning expertise in architectures such as CNNs, RNNs and GANs is highly valuable.
• Familiarity with software engineering principles, Git, testing methods and agile practices is valuable.

Conditions

Remote work, primarily from home.

Base salary range for roles in Georgia, Illinois, North Carolina, Texas and Wisconsin is USD 157,000 to 361,000 per year. Actual offers may vary by location, experience, education, training or skill level, and variable incentives may also be offered.

The company is an equal opportunity employer and will consider qualified applicants with criminal histories as the law requires.

Benefits

• Health, financial and emotional wellbeing benefits, with US benefit details available from the company.
• Career development programs to help you become a subject expert or move into another division.