Job summary
Job post source
This job is directly from JPMorgan Chase & Co.
Job overview
The Sr. Machine Learning Scientist role at JPMorgan Chase & Co. involves applying advanced machine learning techniques to critical technology challenges in cybersecurity, software, and infrastructure, driving innovation within the Chief Technology Office.
Responsibilities and impact
The role requires researching new ML methods, developing state-of-the-art models for business problems, collaborating with partner teams to deploy solutions, driving firmwide ML initiatives, and contributing reusable code components.
Compensation and benefits
The position offers an annual salary range of $164,350 to $260,000 USD, with no additional benefits explicitly mentioned in the description.
Experience and skills
Candidates must have a PhD with 1 year or a Master's with 2 years of relevant experience, strong hands-on expertise in ML and deep learning tools like TensorFlow and PyTorch, experience with large language models and related tools, scientific thinking, big data experience, and strong communication skills; preferred qualifications include a strong math/statistics background, financial industry familiarity, and experience with cloud deployment and published research.
Career development
The job encourages independent learning, research, and experimentation with new ML innovations, offering opportunities to work on complex challenges that can transform the bank's operations.
Work environment and culture
The role is highly collaborative, involving close work with business, technology, and control partners within a strategic innovation team in a major financial institution.
Company information
JPMorgan Chase & Co. is a leading global financial services firm with a focus on technology-driven innovation, particularly through its Chief Technology Office and Applied Innovation of AI team.
Team overview
The candidate will join the elite AI2 team within the Chief Technology Office, working closely with stakeholders in cybersecurity, software, and infrastructure technology groups.
Job location and travel
The position is full-time, on-site in Jersey City, New Jersey, United States.
Unique job features
The job offers unique opportunities to work with cutting-edge ML techniques including large language models, reinforcement learning, and generative AI applied to critical technology infrastructure and cybersecurity challenges.
Company overview
Latinx in AI (LXAI) is a nonprofit organization dedicated to increasing the representation and visibility of Latinx individuals in the artificial intelligence field by fostering community, mentorship, and professional development. LXAI organizes workshops, conferences, and networking events, including prominent gatherings at major AI conferences like NeurIPS and ICML, to connect Latinx researchers, engineers, and students with industry leaders and academic opportunities. The organization sustains itself through sponsorships, partnerships with tech companies, and grants that support its programs and scholarships. Founded in 2018, LXAI has played a significant role in advocating for diversity and inclusion within the global AI community, and candidates should be aware of its collaborative culture and mission-driven focus.
How to land this job
Position your resume to highlight your expertise in machine learning and deep learning frameworks like TensorFlow and PyTorch, emphasizing your hands-on experience with large language models (LLMs) and tools such as LangChain and Vector databases to align with LXAI's cutting-edge AI initiatives.
Showcase your ability to collaborate across cybersecurity, software, and technology infrastructure domains, underscoring your experience deploying machine learning solutions into production and driving scalable, firmwide AI frameworks.
Apply through multiple channels including the Latinx in AI corporate website, LinkedIn job postings, and relevant AI-focused job boards to maximize your application reach and visibility.
Connect with current employees or team members at LXAI on LinkedIn, using ice breakers such as commenting on recent AI research published by the team or expressing genuine interest in their work on generative AI and reinforcement learning projects to initiate conversations.
Optimize your resume for ATS by incorporating keywords from the job description like 'machine learning,' 'deep learning,' 'LLMs,' 'TensorFlow,' 'PyTorch,' 'cybersecurity,' and 'production deployment' to ensure it passes automated screenings effectively.
Leverage Jennie Johnson's Power Apply feature to automate tailored applications, identify optimal application platforms, and discover relevant LinkedIn connections, allowing you to focus your energy on preparing for interviews and further skill development.
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