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Senior Data Scientist / MLOps Engineer (Optimization Specialist)Purple DriveUnited States

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XX

Senior Data Scientist / MLOps Engineer (Optimization Specialist)

Purple Drive
  • US
    United States
  • US
    United States

Über

Mandatory Skills
Optimization Algorithms (Simulated Annealing)
MLOps & ML Pipeline Engineering (Azure preferred)
Production-Grade Python / Model Deployment
Algorithm Design & Variable Optimization
Quantum Annealing / Quantum Computing (Exposure)
Type:
Contract
Industry:
Advanced Analytics / Quantum Computing Research
Job Summary
We are seeking a highly skilled Data Scientist with a strong background in
MLOps Engineering
to lead the development and productionalization of complex optimization models. You will be responsible for not only designing the core models specifically focusing on
Simulated Annealing
and transitioning toward
Quantum Annealing,
but also building the automated pipelines required to move these models into a production environment.
Key Responsibilities
Core Modeling:
Design and develop advanced optimization models. You will lead the "journey" from classical optimization to simulated annealing, with a future-state focus on quantum annealing. MLOps & Productionization:
Bridge the gap between data science and DevOps by writing production-grade code. Ensure models are scalable, reliable, and integrated into the broader ecosystem. Pipeline Construction:
Design and maintain robust data and ML pipelines. You will determine what data is pushed through the system and how it is processed for maximum efficiency. Algorithm Selection:
Lead the selection of algorithms and variables. You must understand how models "reason" and be able to justify the architectural choices for the optimization engine. Deployment:
Take full ownership of the model deployment lifecycle, ensuring that the "Optimization Thing" (internal use case) is fully functional in a live environment. Technical Requirements
Advanced Optimization:
Deep expertise in optimization algorithms, specifically
Simulated Annealing
. Familiarity or interest in
Quantum Annealing/Quantum Computing
is a significant plus. Engineering Excellence:
Proven ability to write
production-ready code
. This is not a research-only role; you must be able to "conscribe" and deploy your own work. MLOps Frameworks:
Strong experience in building and managing machine learning pipelines ( Azure preferred). Data Science Fundamentals:
Mastery of variable selection, algorithm tuning, and model evaluation metrics. Preferred Qualifications
Experience with high-stakes, confidential use cases involving complex data modeling. Local to
Minnesota
(Strongly preferred for onshore collaboration). Ability to work in an agile, fast-paced environment with an "immediate" onboarding timeline.
  • United States

Sprachkenntnisse

  • English
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