Sr. Machine Learning Engineer

Job Title: Sr. Machine Learning Engineer Location: Malvern, PA (Onsite from Day 1) Duration: 12+ Months (High likelihood of multi-year extension)

Experience: 5 - 7 Years

Role Overview

We are seeking a Senior Machine Learning Engineer with strong AWS expertise to design, deploy, and scale advanced ML solutions. This role requires deep knowledge of cloud-native services, modern MLOps practices, and hands-on experience building and optimizing data-driven systems in production.

Key Responsibilities:

Design and deploy ML models (LLMs like GPT, BERT, RAG, and deep learning architectures) using AWS services such as SageMaker, Glue, Lambda, and Redshift.

Build and maintain CI/CD pipelines for ML workflows; automate deployments with MLflow, Docker, and related tools.

Develop scalable data pipelines using PySpark and SQL to handle large, complex datasets.

Write efficient, production-grade code in Python and Java, integrating ML solutions with enterprise systems.

Optimize performance of distributed ML workflows across cloud infrastructure.

Collaborate with cross-functional teams (Data Engineering, Product, Cloud Infrastructure) to ensure reliable and scalable ML solutions.

Required Skills & Experience:

5+ years of experience in Machine Learning Engineering or Applied ML roles.

Strong hands-on experience with AWS services (SageMaker, Glue, Lambda, Redshift).

Proven expertise in deploying and maintaining ML models in production.

Proficiency in Python and Java; solid understanding of data structures and algorithms.

Strong knowledge of MLOps frameworks (MLflow, Docker, Kubernetes).

Experience with big data tools (PySpark, SQL) for ETL and pipeline development.

Familiarity with LLMs, deep learning frameworks (TensorFlow, PyTorch), and distributed training.

Nice-to-Have:

Experience with RAG implementations or vector databases.

Background in large-scale data science or NLP projects.

Knowledge of AWS security, IAM, and cost optimization practices.