AIML Engineer

Job Title: AIML EngineerLocation: Across the USADuration: Long TermVisa: Citizen, GC, H1B & EADExperience: 10+ years
Experience:

• 5+ years of experience in AI/ML development, with a strong focus on RAG, PyTorch, TensorFlow, GenAI technologies, and system-generated models.
• 10+ years of IT experience, showcasing leadership and technical depth.
• Proven track record of building proof-of-concept AI/ML applications and scaling them into enterprise-grade solutions.

Skills:

• Expertise in AI architecture design and development for scalable, enterprise-grade systems tailored to financial applications.
• In-depth understanding of financial systems, regulatory landscapes, and data-driven decision-making.
• Exceptional communication skills with the ability to present technical solutions to diverse audiences, including large groups.

Other:

• Ability to collaborate across teams and lead AI/ML strategy initiatives effectively.

Job Summary:We are seeking a skilled and innovative AI Architect/Engineer to lead AI/ML initiatives, particularly within the finance domain. This role requires deep technical expertise, a strong understanding of financial systems, and proven leadership capabilities. The ideal candidate will architect and implement enterprise-grade AI systems, collaborating across teams to drive impactful solutions that address critical business challenges.
Key Responsibilities:

• AI/ML Development:
• Architect and implement scalable AI/ML solutions to address critical business use cases.
• Drive hands-on development using technologies such as RAG, PyTorch, TensorFlow, GenAI, and system-generated models.
• Finance Domain Applications:
• Develop AI solutions to enhance operational efficiency, cost optimization, and compliance adherence within financial systems.
• Deploy production-ready AI/ML systems tailored to enterprise applications in finance.
• Collaboration and Communication:
• Collaborate with business and IT teams to translate requirements into technical solutions.
• Communicate technical solutions effectively to diverse stakeholders, including large audiences.
• Team Leadership and Mentorship:
• Provide mentorship and guidance to team members, fostering a collaborative environment.
• Grow the team by hiring and mentoring additional resources as workload increases.
• Innovation and Strategy:
• Lead AI/ML strategy development and execution across teams.
• Stay current with industry trends to introduce cutting-edge AI capabilities.
• Design and optimize solutions using vector databases for efficient data retrieval and embedding storage.