AI Platform Architect

Please take a moment to review the job description below. If you find it aligns with your skills and interests, I’d appreciate it if you could apply to the role along with your updated resume & contact details to discuss this opportunity.

Job Role: AI Platform Architect

Location: NYC (Need to work onsite 2 days per week – Need local or willing to relocate to NYC or nearby locations and work onsite)

Duration: Long term

We are seeking an experienced Architect with 12–15 years of software development experience and a proven track record in leading AI/ML initiatives. This role demands hands-on expertise in deploying AI/ML models at scale, proficiency in Generative AI frameworks, and an in-depth understanding of cloud platforms and modern software technologies. The candidate should demonstrate strong business acumen, excellent communication skills, and the ability to design innovative, scalable solutions that align with organizational goals.

Responsibilities:

• Design and develop end-to-end applications that seamlessly integrate machine learning capabilities, including real-time inference, batch processing, and efficient data management to deliver scalable and robust solutions.
• Identify bottlenecks in the model development, deployment, and monitoring process.
• Design and implement production-ready machine learning pipelines, including model training, validation, deployment, and monitoring (e.g., labelled data sets to check performance of prompts).
• Build scalable, high-performance infrastructure to support Generative AI workflows (e.g., distributed training, inference optimization, and GPU/TPU utilization).
• Deploy GenAI applications into production cloud environments with performance, cost, and latency trade-offs considered (e.g., open-source vs. closed-source, quantization, prompt token length, completion caching, prompt caching).
• Monitor and troubleshoot model performance, addressing issues such as performance drift and response latency.
• Stay at the forefront of Generative AI advancements, identifying opportunities to incorporate the latest research and techniques into production systems.

Qualifications:

• Bachelor’s or advanced degree in computer science, engineering, or a related field.
• 3 years of experience in machine learning engineering, with a focus on deploying AI systems at scale.
• Experience working with large-scale Generative AI applications in production environments.
• Relevant experience in the legal domain is a plus.
• Strong proficiency in Python and machine learning frameworks (e.g., TensorFlow, PyTorch).
• Experience with Generative AI tools and techniques (e.g., LLMs, quantization, synthetic data generation, knowledge distillation, retrieval-augmented generation, fine-tuning).
• Proficiency in commons GenAI libraries (e.g., LangChain, Autogen) and cloud-native AI services (e.g., Azure search)
• Knowledge of cloud infrastructure (e.g., Azure) and management tools for IT components, storage, networking, and caching.
• Familiarity with ML Ops principles, including CI/CD pipelines, containerization, and automated testing for AI systems.
• Experience with modern container platforms (e.g., Docker, OpenShift) and tools like Jenkins, Git, and Sonar.
• Strong problem-solving skills with the ability to address complex technical challenges.
• Excellent communication skills to collaborate with cross-functional teams and explain technical concepts to non-technical stakeholders.
• Eagerness to stay updated with cutting-edge AI research and apply innovative ideas to real-world problems.
• Organization and attention to detail, ensuring high-quality delivery.
• Ability to work collaboratively to create innovative and efficient solutions.