Responsibilities
Job Description
Developing data pipelines to collect, process, and analyze diverse datasets at scale.
Designing and implementing deep learning architectures capable of processing large volumes of data.
Analyzing model performance by conducting experiments and tests to evaluate effectiveness and identify prospects for improvement.
Building and managing agentic workflows to support scalable and productive AI/ML solutions.
Optimizing and fine-tuning existing machine learning models to improve performance and effectiveness.
Building and maintaining pipelines to monitor, manage, and continuously improve production machine learning and deep learning models.

Qualifications
A bachelor’s, master’s, or PhD degree in computer science or a related field, with at least 2–6 years of relevant experience.
Experience training, building, and deploying large-scale deep learning models is required.
Experience designing and implementing sequence and time-series models is required.
Expertise in Python,



with hands-on experience using deep learning frameworks such as PyTorch or TensorFlow.
Experience with Git, CI/CD pipelines, and MLOps practices for automating model deployment and managing production machine learning workflows.
Working knowledge of Linux, SQL, Git, and Bash scripting.

Advantages
Our benefits include:
Generous paid time off policies
Savings plans and other financial wellness tools available in each region
Hybrid working opportunities
Free breakfast, lunch, and snacks daily
In-office wellness experiences and reimbursement for select wellness expenses (e.g., gym, personal training and more)
Company-sponsored sports teams and fitness events (JPM Corporate Challenge, Cycle for Survival, Wall Street Rides FAR and more)
Volunteer opportunities and charitable giving
Social events, happy hours, treats, and celebrations throughout the year
Workshops and continuous learning opportunities

Required Skills
['AI/ML']

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