Senior AIML Engineer

AI / ML Engineer

Location: Malven PA

Hybrid Schedule (T/W/th) M and F remote (no flexibility on this at all dont ask)

(If relocating must actually relocate. Cannot commute via flying weekly)

Job Description

We are looking for a Senior AI/ML Engineer who thrives at the intersection of complex mathematics and scalable cloud architecture. You wont 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.

• 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.

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.
  • 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.

• The Architect: Youve 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 arent afraid of complex logic.

Note to Candidates: This role is for a builder who loves the Engineering in Machine Learning Engineering. If you enjoy solving puzzles that involve both high-level mathematics and deep-cloud infrastructure we want to talk to you.