Applied AI ML Lead - DocAI

careful design of libraries and services to be leveraged across the team. This role offers a unique blend of scientific research and software engineering, requiring a deep understanding of both mindsets. The role is initially that of an individual contributor, though there will be optional opportunity for management responsibility depending on the candidate's experience.Job responsibilitiesBuild robust Data Science capabilities which can be scaled across multiple business use cases.Collaborate with software engineering team to design and deploy Machine Learning services that can be integrated with strategic systems.Research and analyse data sets using a variety of statistical and machine learning techniques.Communicate AI capabilities and results to both technical and non-technical audiences.Document approaches taken, techniques used and processes followed to comply with industry regulation.Collaborate closely with cloud and SRE teams while taking a leading role in the design and

delivery of the production architectures for our solutions.Required qualifications, capabilities, and skillsHands-on experience in an ML engineering role.Masters degree or PhD in a quantitative discipline, e.g., Computer Science, Mathematics, Statistics.Track record of developing, deploying business-critical machine learning models.Broad knowledge of MLOps tooling - for versioning, reproducibility, observability, etc.Experience monitoring, maintaining, enhancing existing models over an extended time period.Specialism in NLP or Computer Vision.Solid understanding of fundamentals of statistics, optimization and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, autoencoders, etc.).Extensive experience with PyTorch, NumPy, Pandas.Hands-on experience in implementing distributed/multi-threaded/scalable applications (incl. frameworks such as Ray, Horovod, DeepSpeed, etc.).Able to communicate technical information and ideas at all levels; convey
information clearly and create trust with stakeholders.Preferred qualifications, capabilities, and skillsExperience designing/implementing pipelines using DAGs (e.g., Kubeflow, DVC, Ray).Experience with big data technologies (e.g., Spark, Hadoop).Have constructed batch and streaming microservices exposed as REST/gRPC endpoints.Familiarity with GraphQL.We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs,
as well as mental health or physical disability needs.
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Take a technical leadership position within JPMorgan's Commercial & Investment Bank, where you'll harness cutting-edge AI techniques to revolutionize business decisions and automate processes.As an Applied AI / ML Lead - Vice President - Machine Learning Engineer in the Applied AI ML team at JPMorgan Commercial & Investment Bank, you will be at the forefront of combining cutting-edge AI techniques with the company's unique data assets to optimize business decisions and automate processes. You will have the opportunity to advance the state-of-the-art in AI as applied to financial services, leveraging the latest research from fields of Natural Language Processing, Computer Vision, and statistical machine learning. You will be instrumental in building products that automate processes, help experts prioritize their time, and make better decisions. We have a growing portfolio of AI-powered products and services and increasing opportunity for re-use of foundational components through