Precision AQ

Precision AQ is a life sciences commercialization and healthcare consulting company that helps biopharma companies bring therapies to market and improve patient access. It describes itself as a commercialization partner for biopharma innovators, market access teams, and brand strategists, with expertise spanning access strategy, HEOR, medical communications, market access, data and analytics, branding, investor relations, and omnichannel/product solutions.

Business Consulting and Services
1001-5000

Description

  • Design, develop, fine-tune, and evaluate machine learning, deep learning, and Generative AI models, including Large Language Models (LLMs).
  • Apply supervised, unsupervised, NLP, and deep learning techniques based on the problem context and data constraints.
  • Optimize model performance across accuracy, latency, scalability, and cost.
  • Conduct model evaluation, validation, and benchmarking using large-scale datasets.
  • Use data preprocessing, feature engineering, augmentation, and synthetic data generation to improve model robustness.
  • Design and implement scalable, production-ready AI solutions integrated into existing platforms and workflows.
  • Build, maintain, and improve MLOps pipelines for training, deployment, monitoring, and lifecycle management.
  • Deploy and manage AI applications in cloud environments, including containerization and orchestration where applicable.
  • Monitor production models for drift, degradation, or failure and implement remediation strategies.
  • Partner with product, engineering, data science, and research teams to translate business problems into technical architectures and model designs.

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field.
  • Minimum 3+ years of hands-on experience in an AI/ML or data science role delivering production-deployed solutions.
  • Strong proficiency in Python and SQL; experience building scalable ML/NLP workflows.
  • Deep hands-on experience with machine learning, deep learning, and natural language processing.
  • Experience with Generative AI and Large Language Models, including fine-tuning and evaluation techniques.
  • Working knowledge of data preprocessing, feature engineering, and model validation practices.
  • Experience deploying AI solutions in cloud environments such as Azure, AWS, or GCP.
  • Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
  • Experience building AI solutions in healthcare, life sciences, analytics, or regulated data (preferred).
  • Hands-on experience with MLOps frameworks and monitoring strategies (preferred).
  • Experience integrating AI models into SaaS products or productized services (preferred).
  • Familiarity with distributed systems, APIs, and modern software engineering practices (preferred).
  • Exposure to enterprise AI governance, security, or compliance considerations (preferred).

Benefits

  • Equal Opportunity Employer status with nondiscriminatory hiring practices.
  • Reasonable accommodation available for applicants with disabilities during the application process.
  • Privacy policy and California applicant privacy notice provided for data handling transparency.

Interested in this position?

Apply directly on the company website

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