AI/ML Engineer

A test is mandatory for this. It will test on Python, AWS Lambda, Sagemaker pipelines and Neural network modeling. 

Senior AI/ML Engineer (Mathematics & Optimization)
We are looking for a Senior AI/ML Engineer who thrives at the intersection of complex mathematics and scalable cloud architecture. You won’t just be "using" models; you will be building the pipelines that fuel them and the systems that deploy them.
Our team focuses heavily on optimization and mathematical modeling. We need a practitioner who is comfortable wrangling messy data from disparate sources, performing sophisticated feature engineering, and translating those inputs into high-performance neural networks or optimization engines.

Key Responsibilities
·         End-to-End Pipeline Development: Build and manage data lifecycles—from ingesting data across multiple sources to feature engineering and model inference.
·         Model Implementation: Develop and refine models focused on optimization and neural networks, ensuring they deliver actionable results and high-impact inferences.
·         Cloud Orchestration: Design and maintain robust, serverless, and containerized workflows within the AWS ecosystem.
·         Technical Leadership: Act as a subject matter expert in Python development, ensuring code quality, scalability, and performance across the ML lifecycle.

Technical Requirements
The Core Stack:
·         Expert Python: Deep experience in Python is non-negotiable. You should be comfortable with the standard data science libraries and writing production-grade code.
·         Advanced AWS Proficiency: * Orchestration: Experience with Step Functions, EventBridge, and Lambda for serverless automation.
o    Infrastructure: Solid understanding of IAM (security/roles), S3 (data lakes), and ECS/Elastic Containers.
·         Modeling & Math: Proven track record in mathematical optimization or neural network development. You understand the "why" behind the results, not just the "how."
The "Nice-to-Haves":
·         Experience building and automating SageMaker Pipelines.
·         Direct experience with operations research or complex optimization algorithms.

Your Background
·         The Architect: You’ve successfully delivered multiple projects where you handled the full data-to-inference journey.
·         The Integrator: You know how to connect various data sources and transform raw information into meaningful features.
·         The Optimizer: You have a passion for math-heavy engineering and aren't afraid of complex logic.