At Allstate, great things happen when our people work together to protect families and their belongings from life’s uncertainties. And for more than 90 years our innovative drive has kept us a step ahead of our customers’ evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection. Job Description As a Lead Machine Learning Engineer, you relish the challenge of solving business problems using the latest techniques and tools to bring models to life that deliver business value. You have prior industry experience with machine learning and find fulfillment in teaching and guiding others. You can learn and adapt quickly and are able to use every tool at your disposal-software, algorithms, models, and beyond-to understand and effectively tackle complex problems. You think about modeling in the context of implementation and runtime considerations. You appreciate the difference between training and explaining models, the importance of good metrics, and the tradeoff between exploration and exploitation. You can perceive common structures between seemingly unrelated problems, and can use this to build tools, algorithms, and models with super-linear value. The Team: Allstate Technology Solutions is dedicated to creating a new type of claims handling platform. By leveraging cutting edge technologies, innovative product design and true integration of artificial intelligence functions with emphasis on Generative AI, we will revolutionize what is means to be a Claims organization. Our goal is to create a truly transformational customer experience, while also enabling significant opportunities for operational efficiencies. Become a part of our story. At Allstate Technology Solutions, you’ll find a collaborative and dynamic team focused on exploring new capabilities and pushing the boundaries of what is possible. The team works in a continuous innovation cycle of ideas, research, testing, analysis, and delivery. Qualifications: Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Physics, Mathematics, Statistics, or another quantitative major. A Ph.D. is a plus. Deep understanding of machine learning algorithms and principles. Prior experience working prompting/tuning large-language models Ability to navigate decisions between traditional modeling and GenAI. Ability to work closely with product managers, engineers, and business leaders. Demonstrated experience leading ML teams, managing projects, and mentoring junior data scientists. 5+ years of experience in programming languages like Python, Java, or C++. 5+ years of experience using machine learning frameworks like PyTorch, TensorFlow, or Scikit-learn. Prior experience using natural language processing, computer vision, or knowledge representation and reasoning to solve a business problem. Prior experience using deep learning techniques to solve a business problem. Prior experience using cloud services (AWS, Azure, GCP) is a plus. Prior experience prompting/tuning large-language models is a plus. Skills Artificial Intelligence (AI), Customer Centricity, Digital Literacy, Inclusive Leadership, Learning Agility, Results-Oriented Compensation Compensation offered for this role is $157,600 – 234,400 annually and is based on experience and qualifications. The candidate(s) offered this position will be required to submit to a background investigation, which includes a drug screen. Joining our team isn’t just a job – it’s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. And one where you can impact the future for the greater good. You’ll do all this in a flexible environment that embraces connection and belonging. And with the recognition of several inclusivity and diversity awards, we’ve proven that Allstate empowers everyone to lead, drive change and give back where they work and live. Good Hands. Greater Together. Allstate generally does not sponsor individuals for employment-based visas for this position. Effective July 1, 2014, under Indiana House Enrolled Act (HEA) 1242, it is against public policy of the State of Indiana and a discriminatory practice for an employer to discriminate against a prospective employee on the basis of status as a veteran by refusing to employ an applicant on the basis that they are a veteran of the armed forces of the United States, a member of the Indiana National Guard or a member of a reserve component. For jobs in San Francisco, please click “here” for information regarding the San Francisco Fair Chance Ordinance. For jobs in Los Angeles, please click “here” for information regarding the Los Angeles Fair Chance Initiative for Hiring Ordinance. To view the “EEO is the Law” poster click “here”. This poster provides information concerning the laws and procedures for filing complaints of violations of the laws with the Office of Federal Contract Compliance Programs To view the FMLA poster, click “here”. This poster summarizing the major provisions of the Family and Medical Leave Act (FMLA) and telling employees how to file a complaint. It is the Company’s policy to employ the best qualified individuals available for all jobs. Therefore, any discriminatory action taken on account of an employee’s ancestry, age, color, disability, genetic information, gender, gender identity, gender expression, sexual and reproductive health decision, marital status, medical condition, military or veteran status, national origin, race (include traits historically associated with race, including, but not limited to, hair texture and protective hairstyles), religion (including religious dress), sex, or sexual orientation that adversely affects an employee’s terms or conditions of employment is prohibited. This policy applies to all aspects of the employment relationship, including, but not limited to, hiring, training, salary administration, promotion, job assignment, benefits, discipline, and separation of employment.
Results-oriented scikit-learn Natural language processing (NLP) statistics mathematics Artificial intelligence (AI) Python Amazon Web Services (AWS) Computer Science Azure reasoning Customer orientation physics C++ Google Cloud Platform (GCP) deep-learning Machine Learning Java TensorFlow computer-vision Quick learner Electrical Engineering PyTorch