Horizon Pharma Plc - Pittsburgh, PA

posted 26 days ago

Part-time,Full-time - Senior
Pittsburgh, PA
Management of Companies and Enterprises

About the position

At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering questions related to the practical design and implementation of Artificial Intelligence (AI) technologies and systems. We currently lead a community-wide movement to mature the discipline of AI Engineering for Defense and National Security. As our government customers adopt AI and machine learning (ML) to provide leap-ahead mission capabilities, we build real-world, mission-scale AI capabilities through solving practical engineering problems. This includes discovering and defining the processes, practices, and tools to support operationalizing AI for robust, secure, scalable, and human-centered mission capabilities. We prepare our customers to be ready for the unique challenges of adopting, deploying, using, and maintaining AI capabilities, while also identifying and investigating emerging AI and AI-adjacent technologies that are rapidly transforming the technology landscape. As a Senior Reinforcement Learning Engineer, you will identify, shape, apply, conduct, and lead engineering research that matches critical U.S. government needs. You will work with and lead interdisciplinary teams to turn research results into prototype operational capabilities for government customers and stakeholders. Your role will involve conducting and leading novel prototyping in applied machine learning and artificial intelligence with a focus on Reinforcement Learning and Test and Evaluation. You will collaborate with AI Division leaders and colleagues to plan, develop, and carry out an overall research strategy, influencing the national research agenda regarding future technology. Additionally, you will actively participate on teams of AI/ML engineers, researchers, designers, and technical leads, building relationships and collaborating with external thought leaders, government customers, and other stakeholders to understand challenges, needs, possible solutions, and research and engineering directions. Mentoring and teaching others will also be a key part of your responsibilities, contributing to improving the overall technical capabilities of the team.

Responsibilities

  • Identify, shape, apply, conduct, and lead engineering research that matches critical U.S. government needs.
  • Work with and lead interdisciplinary teams to turn research results into prototype operational capabilities for government customers and stakeholders.
  • Conduct and lead novel prototyping in applied machine learning and artificial intelligence with a focus on Reinforcement Learning and Test and Evaluation.
  • Collaborate with AI Division leaders and colleagues to plan, develop, and carry out an overall research strategy.
  • Actively participate on teams of AI/ML engineers, researchers, designers, and technical leads.
  • Build relationships and collaborate with external thought leaders, government customers, and other stakeholders to understand challenges, needs, possible solutions, and research and engineering directions.
  • Contribute to improving the overall technical capabilities of the team by mentoring and teaching others.

Requirements

  • BS in Computer Science or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years of experience; OR PhD with five (5) years of experience.
  • Experience in applied AI/ML research or engineering activities.
  • Experience with Reinforcement Learning including developing designs, evaluating reward strategies, and assessing learning performance.
  • Strong development experience in designing and implementing software and systems resources for AI/ML prototypes.
  • Strong written and verbal communication skills.

Nice-to-haves

  • Experience with policy gradient methods.
  • Familiarity with autonomy or robotics fields and applying AI to implement control strategies.
  • Experience working with model experimentation software, such as MLFlow or Weights & Biases.
  • Experience building applications in Cloud platforms (Azure, AWS, Google Cloud Platform).
  • A track record of synthesizing lessons learned from research or engineering activities for publication.

Benefits

  • Health insurance
  • Dental insurance
  • 401k retirement plan
  • Flexible scheduling
  • Paid holidays
  • Professional development opportunities
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