MLOps 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.

• Develop and implement end-to-end MLOps strategies to enhance solutions, including building, testing, and deploying machine learning and deep learning models.
• Design, build, and maintain robust machine learning pipelines for production environments, ensuring seamless integration with operational processes.
• Process and transform source data for machine learning pipelines, utilizing cloud computing platforms to enhance efficiency and scalability.
• Collaborate with cross-functional teams to assess and apply AI technologies to address complex business problems, focusing on practical implementations and operationalization.
• Communicate technical findings and insights to stakeholders and work closely to develop actionable solutions that meet customer needs.
• Develop and maintain comprehensive code and model documentation, and support model governance and compliance approvals.
• Adhere to best coding practices and standards in Python, including effective use of Git Hub for version control and collaborative development.
• Prepare and deliver presentations, including written reports and visual presentations, to communicate analysis results and recommendations to leadership.

• 5+ years of experience in machine learning and data science, with a focus on operationalizing models and managing MLOps workflows.
• 5+ years of hands‑on experience with Python, classical machine learning methods, and deep learning frameworks such as Scikit-learn, PyTorch, Tensor Flow.
• 5+ years of experience leading MLOps projects, demonstrating strong technical communication skills and technical leadership.

• Experience with NLP techniques, including text embedding, text classification, and the use and evaluation of LLMs/generative AI models.
• Experience with distributed computing frameworks such as Apache Spark.
• Experience with distributed machine learning model training using Azure
  
  ML or Databricks platforms.
• Expertise in building and tuning weighted model ensembles in online learning contexts.
• Experience in forking and modifying open-source projects to meet specific needs.
• Proven track record of working on collaborative software projects using Git Hub.
• Extensive programming experience with Python and PySpark.
• Experience with machine learning and deep learning frameworks:
  Scikit-learn, PyTorch, Tensor Flow.
• Proven production ML delivery (MLOps, CI/CD).
• Ability to bridge data science and engineering teams.

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: $140,000 - $180,000. In addition, you may be eligible for a discretionary bonus for the current performance period.

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…