Our client is looking for an experienced Senior Generative AI Engineer to help build and maintain APIs and SDKs to train, fine-tune, and access AI models at scale. You will work as part of their Enterprise AI team and build systems that will enable our client's users to work with Large-Language Models (LLMs) and Foundation Models (FMs), using their public cloud infrastructure. You will work with a team of world-class AI engineers and researchers to design and implement key API products and services that enable real-time customer-facing applications.
Our client is open to hiring a Remote Employee for this opportunity
Job Responsibilities
Examples of projects you will work on include:
- Architect, build and deploy well-managed core APIs and SDKs to access LLMs and our client's proprietary FMs including training, fine-tuning and prompting tasks, including orchestration SDKs.
- Design APIs for performance, real-time applications, scale, ease of use and governance automation.
- Develop application-specific interfaces that leverage LLMs and FMs to continue to enhance the associate and customer experience.
- Enable our client's users to build new GenAI capabilities.
- Develop tools and processes to monitor API access patterns and operational health.
- Design and implement AI safety and guardrails in the API layer working closely with researchers.
Basic Qualifications:
- Bachelor’s degree in Computer Science, Computer Engineering or a technical field
- At least 4 years of experience designing and building and deploying ML application platforms.
- At least 4 years of experience programming with Python, Go, Scala, or Java
- At least 1 year of experience building, scaling, and optimizing training or inferencing systems for deep neural networks
Preferred Qualifications:
- Familiarity with building large-scale AI products or platforms for NLP, speech, computer vision, or recommendation systems serving millions of users.
- Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines.
- Experience at tech and product-driven companies/startups preferred.
- Ability to iterate rapidly with researchers and engineers to improve a product experience while building foundational capabilities.
- Familiarity with deploying large neural network models in demanding production environments.
- Have experience with API security, observability, cloud access control, and privacy best practices.
- Keen attention to following production standards and practices.
- Passionate about ML optimizations and open-source technologies.
About Company
Our client's mission is to create trustworthy, reliable, and human-in-the-loop AI systems, changing banking for good. For years, our client has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real-time, our client's applications of AI & ML are bringing humanity and simplicity to banking. Because of their investments in public cloud infrastructure and machine learning platforms, they are now uniquely positioned to harness the power of AI. They are committed to building world-class applied science and engineering teams and continue their industry-leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. While working for our client, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve their customers and businesses who have come to love the products and services we build.
At this time, our client will not sponsor a new applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount our client is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based on the agreed-upon number of hours to be regularly worked.
- New York City (Hybrid On-Site): $165,100 - $188,500 for Senior Machine Learning Engineer
- Remote (Regardless of Location): $140,000 - $159,800 for Senior Machine Learning Engineer
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
This role is also eligible to earn performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI). Incentives could be discretionary or non-discretionary depending on the plan.
