We are looking for an experienced AI/ML Engineer to join our Applications team within our platform engineering group. In this role, you'll be responsible for designing, building, deploying, and maintaining production-grade AI systems and ML pipelines. You'll translate cutting-edge data science research into practical, scalable solutions, handling model deployment both in cloud environments and on-premises using GPUs and CUDA. Youll optimize and implement ML models, workflows, and AI agents to ensure high performance and reliability in production environments.
Responsibilities:
Design, implement, and deploy ML models, AI-driven applications, AI workflows, and LLM-based agents into production.
Build, manage, and maintain robust ML pipelines and systems.
Deploy models on cloud and on-premises GPU servers.
Optimize system performance, including model inference, scalability, and resource utilization both on cloud and on-premises.
Develop and maintain services, APIs and integrate ML models into microservices-based applications.
Collaborate with cross-functional teams including data science, backend, DevOps, and platform teams.
Stay up to date with the latest developments in AI, machine learning, and related fields, focusing on LLMs, exploring how emerging technologies can be applied to improve products and services.
Responsibilities:
Design, implement, and deploy ML models, AI-driven applications, AI workflows, and LLM-based agents into production.
Build, manage, and maintain robust ML pipelines and systems.
Deploy models on cloud and on-premises GPU servers.
Optimize system performance, including model inference, scalability, and resource utilization both on cloud and on-premises.
Develop and maintain services, APIs and integrate ML models into microservices-based applications.
Collaborate with cross-functional teams including data science, backend, DevOps, and platform teams.
Stay up to date with the latest developments in AI, machine learning, and related fields, focusing on LLMs, exploring how emerging technologies can be applied to improve products and services.
Requirements:
At least 4-5 years of experience in building ML/AI solutions, specifically in production environment
Strong experience in building and maintaining scalable machine learning infrastructures
Strong proficiency in Python
Solid understanding of Data Science and Machine Learning lifecycle and best practices for model deployment and serving
Excellent problem-solving abilities, coupled with a creative and strategic mindset
Extensive experience with ML frameworks
Understanding of microservice design and architecture
Proven ability to work effectively in a team setting
Advantages:
Familiarity with distributed ML tools
Experience with real-time machine learning model deployment.
Familiarity with cybersecurity applications of machine learning
Advanced skills in performance optimization for high throughput systems
Tech Stack:
AWS (SageMaker, Lambda), PyTorch, vLLM, Ray, Hugging Face, Docker, Kubernetes, FastAPI, Flask.
At least 4-5 years of experience in building ML/AI solutions, specifically in production environment
Strong experience in building and maintaining scalable machine learning infrastructures
Strong proficiency in Python
Solid understanding of Data Science and Machine Learning lifecycle and best practices for model deployment and serving
Excellent problem-solving abilities, coupled with a creative and strategic mindset
Extensive experience with ML frameworks
Understanding of microservice design and architecture
Proven ability to work effectively in a team setting
Advantages:
Familiarity with distributed ML tools
Experience with real-time machine learning model deployment.
Familiarity with cybersecurity applications of machine learning
Advanced skills in performance optimization for high throughput systems
Tech Stack:
AWS (SageMaker, Lambda), PyTorch, vLLM, Ray, Hugging Face, Docker, Kubernetes, FastAPI, Flask.
This position is open to all candidates.
