About Us:
We believe that making the best decisions means looking at all the facts – a near-impossible task in our era of information overload. To fix this, we are building the next generation of machine learning software. Powered by generative AI, our algorithms analyze key information sources and provide comprehensive, factual answers for even your most complex queries.

We believe that the transformative impact of generative AI will be only realized by those willing to take on the world's biggest information challenges. To make this future come true, we deploy our longstanding expertise in reinforcement learning and natural language processing.

We are scientists. Builders. Entrepreneurs. We spearheaded many of AI's most impactful applications. We led teams at Google, DeepMind, and EY Parthenon. We now bridge cutting-edge AI research and the biopharma industry.

About the role:

We are looking for a senior engineer who brings experience in both software engineering and machine learning infrastructure, and who can work on technically challenging ML problems. You will work closely with cross-functional teams to design and deploy ML algorithms, models, and systems that drive insights and automation within our platform. One of your key roles will be to optimize the performance of our machine learning systems, both training and inference. Finally, you should be fluent in Pytorch, Tensorflow or Jax and have previously implemented deep learning algorithms in one of those frameworks.

What you'll do:

• Generative AI Development: Research, design, and implement generative models, in particular language models, for information extraction and data analysis.
• Algorithm Development: Research, design, and develop machine learning models and algorithms optimized for high-recall and high-accuracy use cases.
• Data Processing: analyze large datasets to extract meaningful insights for improving and serving the output of generative models.
• Model Training: Train and improve generative models using state-of-the-art supervised and reinforcement learning techniques.
• Model Deployment: Implement and deploy machine learning models using standard deep learning libraries and toolsets (Pytorch; Tensorflow or Jax experience a plus), in a scale-up, real-time production setting on large Cloud computing platforms.
• Continuous Improvement: Monitor model performance, identify areas for improvement and iterate on existing solutions to enhance accuracy and efficiency.
• Collaboration: Collaborate with software engineers, product managers, and stakeholders to integrate machine learning features into our data platform.
• Research & Innovation: Stay up-to-date with the latest developments in machine learning. Quickly build prototypes to create user engagement and find new ways to assist users with their day-to-day tedium using generative models.
• Documentation: Maintain detailed documentation of ML models, processes, and solutions for future reference.
  

What you'll bring:

• Bachelor's, Master's, or PhD degree in Computer Science, Machine Learning, Data Science, or a related field.
• Proven experience (5+ years) in designing and implementing machine learning models, preferably with product-facing experience.
• Expert proficiency in Python or a related programming language.
• Strong proficiency in a machine learning framework such as PyTorch, TensorFlow, or Jax.
• Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment.
• Excellent communication skills to explain complex technical concepts to the broader software development team and non-technical stakeholders.
• A solid understanding of statistical modeling and data analysis techniques is a plus.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.