Pfizer Machine Learning/NLP Engineer in Collegeville, Pennsylvania
The Pfizer Machine Learning and Intelligent Assistance Team, builds, delivers and maintains the products, platforms and capabilities that enable Pfizer Business Units to leverage intelligent automation solutions to effectively engage/collaborate with teams internally and our customers externally. We build advanced AI technology solutions at a global scale that positively impact Pfizer business performance. Pfizer is accelerating the use of AI technologies across our entire enterprise.
We are looking for a natural language processing (NLP) engineer to join the Intelligent Solutions Team to scale and help us improve our NLP products and create new efficient self-learning NLP applications and products.
You will need to apply state of the art NLP and ML techniques, build robust pipelines to enable end to end intelligent solutions for unique business problems. You will be responsible for developing the NLP vision for new projects and will need a keen understanding of NLP/ML models, solutions and technologies. Finally, you will also assist in evangelizing AI/ML/NLP across Pfizer and promote adoption and enablement of NLP solutions across Pfizer by providing education, guidance and mentorship to junior members of the team and the broader Pfizer digital and business community.
The ideal candidate will be passionate about health care, software engineering, machine learning, NLP and stay up-to-date with the latest developments in the field.
Understand business problems/objectives and develop strategy/roadmap to pilot and build NLP based software products that help to achieve business goals for business clients
Lead the development of robust NLP and machine learning pipelines to deliver stable and efficient production-ready components and solutions.
Articulate experiment plans that demonstrate the process of model building, refinement and productization
Supervise the data acquisition process if more data is needed
Find available datasets online that could be used for training
Define validation strategies
Define the preprocessing or feature engineering to be done on a given dataset
Define data augmentation strategies
Train models and tuning their hyperparameters
Analyze the errors of the model and design strategies to overcome them
Deploy models to production
Present model outcomes in a scientifically rigorous manner
Produce executive reports and visualizations for decision makers throughout the organization
Directly engage with key business stake-holders (Director/Sr. Director level)
Lead projects with vendor resources and business stakeholders from requirements gathering through the full software development life cycle.
Shared-ownership of advancing team's capabilities in Machine Learning and NLP.
Managerial responsibility for up to five interns and contingent workers
Masters degree in Data Science, Computer Science, Informatics, life sciences, physics, applied mathematics, statistics or related field
5 years as a data scientist, Machine Learning or NLP engineer
5 years working with different types of enterprise and real world data sets - structured, semi-structured and unstructured data
4 years building ML/NLP based software solutions
Deep understanding and workings of contextual search products and solutions
Strong understand of Software Engineering and Development Life Cycle principles
Expertise in supervised and unsupervised Machine Learning techniques, with emphasis on Natural Language Processing (NLP)
Experience building production-ready NLP systems, from preprocessing and normalization to monitoring model drift in a production environment, ideally using NLP libraries and technologies including Spacy, PyTorch & Deep Learning models
Proficiency in leveraging cloud-based machine learning resources such as those from Amazon Web Services or Google Cloud for model training and productization
Expertise in NLP feature engineering and modeling (e.g., text classification, entity recognition, dependency parsing)
Experience with SoTA modeling techniques, such as transformers (e.g., BERT, GPT-N),
Experience in applying NLP in multi-lingual and multi-modal contexts
Experience taking an NLP project from concept to production
Expertise with Python
Building deep neural networks with modern tools, such as PyTorch or Tensorflow
Building, testing, and deploying computer vision based solutions
Writing unit tests
Collaborating via Git
Ability to thrive in a fast-paced multi-disciplinary environment; with the ability to effectively communicate with a diverse audience
Experience with hyperparameter optimization, model selection and validation.
Experience with implementation of solutions with DevOps tools within the CI/CD pipeline (eg. Docker, Kubernetes)
Good proficiency with SQL, Python, Scala, or Java as well as formal statistical tools R, SAS, etc.
Excellent written and verbal communication skills
Strong Analytical Thinking and Problem Solver.
NON-STANDARD WORK SCHEDULE, TRAVEL OR ENVIRONMENT REQUIREMENTS
Flexibility to work across multiple time zones (i.e.: EST, PST, GMT, IST)
Eligible for Employee Referral Bonus
Pfizer requires all U.S. new hires to be fully vaccinated for COVID-19 prior to the first date of employment. As required by applicable law, Pfizer will consider requests for Reasonable Accommodations.
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EEO & Employment Eligibility
Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer.
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