New

Contract, AI & Machine Learning Fellow

PTC Therapeutics, Inc
United States, New Jersey, Warren
500 Warren Corporate Center Drive (Show on map)
Jan 17, 2025
Job Description Summary: PTC is proud to present the Talent Pipeline Program, a pioneering initiative aimed at cultivating the next generation of industry leaders. With a legacy of 26 years marked by resilience, innovation, and success, PTC understands the importance of investing in talented individuals who exhibit persistence and a strong work ethic. The Talent Pipeline Program is a one-year comprehensive training and real-world work experience opportunity tailored for recent university graduates. This program is designed to bridge the gap between academic knowledge and professional application, equipping participants with the skills and experience necessary to excel in their careers. At PTC, we believe in nurturing talent and providing a supportive environment where recent graduates can thrive. The Talent Pipeline Program is our commitment to empowering the next generation and investing in a brighter future for all. . Job Description: Job Objective The Contract, AI & Machine Learning Fellow, will be responsible for assisting in the design, implementation, and maintenance of all components associated with custom machine learning development - including database work, data processing, model development, and testing. The focus of this role is to help deliver autonomous solutions that accelerate business initiatives and productivity, while ensuring that the solution is both maintainable and scalable to future needs. Tasks/Responsibilities Under minimal supervision, design, implement, and document machine learning systems to perform predictive modeling oncomplex problems with multi-layered data sets. Contribute towards building automated, user-friendly systems, reports, dashboards, etc. that will support business needs and future growth. Maintain a broad knowledge of state-of-the-art principles and techniques that may contribute towards the identification of new project areas or technologies. Determine operational feasibility of machine learning applications by evaluating the problem definition, requirements, and proposed solutions. Experience / Qualifications Bachelor's degree in computer science, computer engineering, or equivalent with some graduate level coursework in machine learning. Candidate pursuing a Master's or PhD in computer science, data science, machine learning, or equivalent. Experience in coding and building ML solutions with hands-on exposure to software and data engineering; including database work, data processing, and model development. Knowledge of math, statistics, data structures and algorithms. Familiarity with deep learning frameworks and libraries. Strong source control (Git), code quality, and refactoring mindset. Generalist, who can get up-to-speed quickly with new technologies through self-paced learning and online research. Analytical thinker with excellent critical thinking, problem-solving, and troubleshooting skills. Excellent planning, organization, and time management skills including the ability to support and prioritize multiple projects. This is a one (1) year Talent Pipeline Program and the candidate/applicant must be able to complete the entire one-year program Fellow must be a recent college graduate. For consideration, each applicant MUST answer the three (3) questions below in your cover letter to be considered for this one-year PTC Talent Pipeline Program. Why do you want to be part of this program? In what ways do you believe you can impact the future? What interests you most about this opportunity? #LI-NM EEO Statement: PTC Therapeutics is an equal opportunity employer. We welcome applications from all individuals, regardless of race, color, national origin, gender, age, physical characteristics, social origin, disability, religion, family status, pregnancy, sexual orientation, gender identity, gender expression, disability, veteran status or any unlawful criterion under applicable law. We are committed to treating all applicants fairly and avoiding discrimination. Click here to return to the careers page