AI and ML Solution Architect

Description

The company helps other businesses connect, protect and analyze their data and applications, from the edge to the cloud, so they can act on what they learn quickly.

This is a hybrid role in AI and machine learning engineering, at subject matter expert level. Your work shapes technical parts of products, solutions and services on a steady, lasting basis.

You will turn customer needs and industry trends into AI and ML products, solutions and system improvements, and decide for yourself the best way to reach each goal. You will also advise functional and technical project teams and may join cross-functional initiatives.

Responsibilities

• Work with cross-functional teams to understand business needs, then choose the algorithms, models and frameworks and design the system for scale, efficiency and robustness.
• Build, implement and tune machine learning models and algorithms, covering data pre-processing, feature engineering, model selection, hyperparameter tuning and training on large datasets, and keep raising their performance and accuracy.
• Put models into production with attention to scale, performance and security.
• Connect models to existing software and infrastructure so they run smoothly and work together.
• Watch deployed models, gather metrics and analyze the results, then refine models and algorithms to improve the system.
• Lead design reviews that keep work aligned with project requirements and best practice.
• With the engineering manager and team lead, set design and implementation standards and keep improving them.
• Lead team meetings to keep the group collaborative and productive.
• Mentor and give feedback to junior and mid-level engineers, offering technical leadership and guidance.
• Spot and fix challenges early, before they grow.
• Use data mining, data modeling, natural language processing and machine learning to pull information out of datasets.
• Follow new AI and ML research, frameworks and algorithms, and test cutting-edge techniques on hard problems and on existing models.
• Prepare strategic presentations and reports for senior stakeholders, with insights and recommendations covering both technical and business points.

Requirements

• Bachelor's or master's degree in computer science, engineering, data science, machine learning, artificial intelligence, or a closely related quantitative field.
• Typically 7-10 years of experience.
• Deep knowledge of machine learning algorithms, including linear regression, decision trees, support vector machines, random forests, deep learning models such as neural networks, and reinforcement learning.
• Skilled at model selection, hyperparameter tuning and judging model performance with suitable metrics.
• Strong grounding in linear algebra, calculus, probability and statistical concepts, applied to building complex models and algorithms.
• Proficient in Python, R or Java, with experience writing production-level code.
• Working knowledge of software engineering practice, including version control such as Git and standard development methodologies.
• Advanced deep learning experience, including convolutional neural networks, recurrent neural networks and transformers, plus transfer learning, generative models and deep learning optimization algorithms.
• Experience doing research, exploring emerging technologies and finding where state-of-the-art methods solve real problems.
• Excellent communication for working with cross-functional teams and stakeholders.
• Strong problem solving and critical thinking to guide projects, make strategic calls and solve hard technical problems.
• Strong programming in Python, R or Java is necessary, and experience with TensorFlow, PyTorch or sci-kit is essential.
• Plus: knowledge of libraries and frameworks such as TensorFlow, PyTorch, sci-kit and Keras.
• Highly preferred: deep understanding of statistical modeling, data mining and data visualization.

Conditions

Hybrid setup: you work on average 2 days a week in an office of the company.

Based in the United States, job level TCP04, in the engineering job family.

Base salary of USD 160,000 to 325,000 in California and USD 141,000 to 325,000 in Texas. The ranges cover base salary only.

Variable incentives can come on top of base pay.

Final offers can fall outside these ranges depending on location, years of experience, education or training, and skill level.

The company is an equal opportunity employer that follows laws on the use of arrest and conviction records.

Benefits

• Health and wellbeing benefits covering physical, financial and emotional health for you and your family.
• Career development programs to help you reach your goals, whether that means becoming a recognized expert in your field or moving into another division.
• Full US benefit details are available on the company's new hire enrollment site.