Machine Learning Engineer

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This range is provided by Fractal. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$/yr - $/yr

Machine Learning Engineer

Fractal Analytics 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 empowers imagination with intelligence.

And that it will be such Fractalites that will continue to build the company for the next 100 years.

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

*** Please note that this role is specifically located in the San Francisco Bay Area and requires 100% onsite availability. If you are not local, we provide weekly travel or relocation.**
* Role Overview :

As an ML Engineer at Fractal Analytics, you will be at the forefront of building and deploying AI-driven solutions that address critical business challenges across industries. You’ll work with cutting-edge AI platforms to develop both custom and pre-built enterprise applications, tackling key problems such as demand forecasting, asset reliability planning, and inventory optimization.

Your role will focus on implementing scalable, production-ready machine learning solutions that seamlessly integrate into our clients' operations. You’ll collaborate with cross-functional teams, optimize model performance, and ensure the reliability and efficiency of AI applications in real-world business environments. If you're passionate about transforming businesses with AI and thrive in a dynamic, impact-driven environment, we’d love to have you on our team.

Responsibilities Include:

• Research, design, implement, and deploy Machine Learning algorithms for enterprise scale applications.

• Engage with clients to translate business needs into technical requirements and Machine Learning solutions.

• Contribute to the design and implementation of features for new and existing enterprise AI solution offerings.

• Provide ongoing support and monitoring for solutions running in production.

• Continuously research and stay abreast of the latest advancements in machine learning and AI to apply cutting-edge techniques in our solutions.

Qualifications:

• MS in Computer Science, Electrical Engineering, Data Science, Statistics, Mathematics, or a related field with a strong emphasis on Machine Learning or Artificial Intelligence.

• Excellent programming skills in Python

• Strong proficiency in Python and ML frameworks like Tensor Flow, PyTorch, or Scikit-learn.

• Applied Machine Learning and AI experience in a professional setting.

• Broad knowledge on ecosystem of machine learning and AI algorithms, including tradeoffs to consider and when most appropriate to use.

• Demonstrated project expertise in supervised/unsupervised learning techniques, deep learning, time series, operations research, or Generative AI.

• Familiarity with ML model lifecycle including key considerations and relevant tools (MLFlow, Air Flow, Kubeflow, etc.) for supporting and governing models at scale.

• Familiarity with scalable AI technologies such as (Map Reduce, Spark, streaming).

• Prior exposure to cloud computing services like AWS, Azure, or Google Cloud is advantageous (especially ML and AI toolkits).

• Ability to drive a project and work both independently and in a team.

• Smart, motivated, can-do attitude, and seeks to make a difference.

• Excellent verbal and written communication.

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…