AI Solutions Architect

SLB; Menlo Park (CA); Hybrid; USD 228,943 - 231,600; Full time

Job summary

SLB is seeking a full-time AI Solutions Architect responsible for leading technology development in AI and machine learning. The role emphasizes modern deep learning methods and collaboration with cross-functional teams. Required qualifications include a Master’s degree in Operations Research or related STEM fields and at least three years of experience in AI/Data Science roles. The position includes travel and allows for some telecommuting within geographic bounds. Compensation ranges from $228,943 to $231,600 annually.

Qualifications

• Master's degree in Operations Research, Industrial Engineering, Applied Mathematics, or Computer Science required.
• 3 years post-baccalaureate experience in AI/Data Science.
• Advanced knowledge in machine learning algorithms and data analytics.

Responsibilities

• Conduct undirected technology development tackling open-ended AI/ML problems.
• Research and assess next-generation technologies for prediction and optimization.
• Communicate sophisticated AI concepts effectively to stakeholders.
• Integrate AI solutions into business workflows with software engineers.
• Mentor junior team members and promote standards and best practices.

Skills

AI and Data Science in Decision Science and Operations Research

Markov decision process

Data Mining for Analytics and Decision Making

LLL based GenAI solution development

Visual LM and Small LM system development

Modern NLP development in AI

Computational intelligence

Time-series Analysis

Applied mathematics statistics

Cloud development tools

Optimization Solver tools including CPLEX

Programming languages (Python, R, Tensorflow, PyTorch)

Education

Master’s degree in a relevant STEM field

Job description

Full-time or part-time: Full-time

Job title: AI Solutions Architect

Job Location: 640 W California Ave, Suite 210, Sunnyvale, CA 94086

Job Description

Responsible for conducting undirected technology development and tackling open-ended AI/ML problems and questions. Participate in data science, artificial intelligence, machine learning, and industrial analytics, with specific emphasis on modern deep learning methods, foundation models, generative AI, and modern decision science solutions. Work with subject‑matter experts, product champions, product managers, and designers to engineer the appropriate system solutions for SLB in the Energy domain. Communicate sophisticated AI concepts to management, clients, and the business community. Research and assess next‑generation technologies for inference, predictive modeling, general‑purpose data‑driven modeling, and optimization of complex systems. Demonstrate advanced working knowledge and experience with data analytics, machine learning algorithms, and optimization methods. Work with software engineers to integrate AI solutions in business workflows. Generate innovative ideas, establish new technology development directions, and shape and execute technical projects. Maintain state‑of-the-art knowledge and contribute to technical discussions and reviews as an expert in related areas of responsibility. Communicate ideas, plans, and results effectively via oral and written reports. Works effectively with peers, management, operations groups, and outside organizations. May participate in the relevant technical reviews and audits of the projects. Review, mentor, and coach junior team members while defining and promoting the use of standards, best practices, and lessons learned. Work across multiple cross‑functional teams in high‑visibility roles to prototype end‑to‑end data solutions. Actively disseminate knowledge via Webinars, talks, and tutorials for the technical community within the company.

Minimum Education & Experience Requirements

Master’s degree in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or a related STEM field, or a foreign equivalent plus 3 years post‑baccalaureate experience in a job offered or any AI/Data Science related job titles.

1. AI and Data Science in the Decision Science and Operations Research space using software implementation technology
2. Markov decision process
3. Data Mining for Analytics and Decision Making
4. LLL based GenAI solution development
5. Visual LM and Small LM system development
6. Modern NLP development in AI
7. Computational intelligence and non‑convex optimization techniques
8. Time‑series Analysis techniques with Statistics and AI
9. Applied and mathematics statistics
10. Cloud development tools and working in cloud environments for AI, Data Mining and Large Scale data systems
11. Optimization Solver tools including CPLEX
12. Programming languages for modern AI and Data Science (Python, R, Tensorflow, PyTorch)

Travel & Telecommuting Requirements

5–10% domestic and international travel required for internal workshops and project work sessions, workshops, conferences, and customer presentations.

Telecommuting permitted less than 50% per week within the same geographic location as the assigned Schlumberger office location.

Compensation

$228,943–$231,600 per year