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Senior AI Engineer

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets; an ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner.

Please visit Fractal | Intelligence for Imagination for more information about Fractal.

Location: Dallas, Texas

Role Overview

Are you a talented and motivated AI engineer with a passion for cutting-edge technology? Do you thrive in a dynamic environment where innovation and collaboration are key? If so, we have the perfect opportunity for you!

As a Senior Simulation / Applied AI Engineer, you will be at the forefront of developing state-of-the-art controls algorithms using deep reinforcement learning and simulation. Your work will directly impact the optimization of industrial processes, making them more efficient and effective. You will create and validate simulations, apply advanced AI techniques, and test the solutions in live factory environments. You will collaborate with a team of top-notch engineers and researchers to bring your solutions to life.

Responsibilities

  • Develop and deploy AI models leveraging a strong background in Python programming.

  • Create and validate simulations of industrial processes using differential equations, state-space representations, or other methods.

  • Apply deep reinforcement learning to optimize the performance of manufacturing systems.

  • Design, implement, and maintain data pipelines for various purposes, including ETL processes, model scoring, model performance monitoring, data offloading, job scheduling, and automation.

  • Conduct experiments, analyze data, and report results to improve AI model performance.

  • Work with subject matter experts to troubleshoot issues and improve AI systems.

  • Collaborate with cross-functional teams to integrate AI solutions into existing infrastructure and workflows.

  • Manage a codebase using version control systems like Gitlab (or Git) and participate in CI/CD pipeline activities.

Required Qualifications

  • Deep expertise in Python and software development practices.

  • Experience writing production-quality code and working with medium to large codebases.

  • Ability to conduct experiments, analyze data, and report results.

  • Understanding of systems dynamics and how to model and simulate them using differential equations, state-space representations, or other methods.

  • Knowledge of machine learning techniques, such as supervised learning, unsupervised learning, computer vision, deep reinforcement learning, etc.

  • Excellent communication and teamwork skills and a passion for learning and innovation.

  • Proven track record of building real-world machine learning solutions.

  • An advanced degree in applied mathematics, engineering (mechanical engineering, aerospace engineering, industrial engineering, chemical engineering), computer science, or a physical science.

Good to Have

  • Familiarity with controls concepts.

  • Experience working with deep reinforcement learning.

  • Experience with distributed deep learning systems.

Why Join Us?

  • Impact: Your work will directly contribute to the optimization of industrial processes, making a measurable difference on real world problems.

  • Growth: We offer opportunities for continuous learning and professional development.

  • Collaboration: Be part of a dynamic team that values innovation and collaboration.

  • Innovation: Work on cutting-edge technology and stay at the forefront of AI and machine learning.

Pay:

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.  The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled.  At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case.  A reasonable estimate of the current range is: $132,000 - $155,000. In addition, for the current performance period, you may be eligible for a discretionary bonus.

Benefits:

As a full-time employee of the company or as an hourly employee working more than 30 hours per week, you will be eligible to participate in the health, dental, vision, life insurance, and disability plans in accordance with the plan documents, which may be amended from time to time.  You will be eligible for benefits on the first day of employment with the Company.  In addition, you are eligible to participate in the Company 401(k) Plan after 30 days of employment, in accordance with the applicable plan terms.   The Company provides for 11 paid holidays and 12 weeks of Parental Leave. We also follow a “free time” PTO policy, allowing you the flexibility to take time needed for either sick time or vacation.

Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

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Salary

$132,000 - $155,000

Yearly based

Location

Texas

Job Overview
Job Posted:
1 week ago
Job Expires:
Job Type
Full Time

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