Executive Director - Solutions Engineering Lead
- Lead and mentor a team of Solutions Engineer and data scientists, fostering innovation and collaboration.
- Provide technical expertise empowering our internal clients to design and deploy Machine Learning, Gen AI, and Agentic systems.
- Leverage your extensive ML experience to guide internal clients in their application development journey considering performance, evaluation, monitoring, resiliency and controls.
- Develop a deep understanding of firmwide standards for Model and Software Development Lifecycles and Information Security Controls.
- Anticipate risks associated with machine learning solutions and prediction/classification systems and strategize mitigation.
- Foster a transparent cross-functional partnership with product management, engineering and client engagement and influence peers and team members to uphold these standards.
- Lead presentations, whiteboard sessions, and technical workshops, effectively communicating the value, differentiators and capabilities of our solutions.
- Communicate complex issues clearly and credibly to senior management and stakeholders.
Required qualifications, capabilities, and skills
- 8+ years of experience or equivalent expertise delivering products, projects, or technology applications.
- Proficiency in programming languages such as Python, R, or Java, with a strong emphasis on Python.
- Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, and industry leading GenAI models.
- Strong skills in data manipulation and analysis using tools like Pandas, NumPy, and SQL.
- Experience in developing, training, and deploying machine learning models, Gen AI models and including knowledge of model evaluation and optimization techniques.
- Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), and microservices design, implementation, and performance optimization.
- Experience with big data technologies like Hadoop, Spark, or Apache Kafka for handling large datasets.
- Proficiency in using version control systems like Git.
- Experience in building and consuming APIs and working with microservices architecture.
- Understanding DevOps and MLOps practices for automating and streamlining the machine learning lifecycle.
- Strong foundation in mathematics and statistics, including knowledge of linear algebra, calculus, probability, and statistical methods.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans Base Pay/Salary
New York,NY $180,500.00 - $285,000.00 / year
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