Senior AI/ML Engineer - Hybrid

NTT DATA Services•Pine Grove Township, PA

13d•$87,120 - $151,250•Hybrid

About The Position

We are seeking a Senior AI/ML Specialist to lead the design, development, and deployment of advanced machine learning and generative AI solutions. In this role, you will work at the forefront of AI innovation—building scalable ML pipelines, fine‑tuning LLMs, shaping AI strategy, and guiding teams as we deliver high‑impact, data‑driven products. If you thrive in a fast‑moving environment and enjoy solving complex technical challenges, this is an opportunity to influence architecture, mentor others, and drive meaningful AI transformation.

Requirements

7+ years of overall experience in software engineering, data science, or machine learning.
3+ years of hands‑on Python experience, including data manipulation with Pandas, NumPy, and scikit‑learn.
2+ years of experience with machine learning frameworks such as TensorFlow and PyTorch.
2+ years of experience working with frameworks like LangChain or LangGraph for LLM integration.
Expertise with ML and deep learning libraries such as PyTorch, TensorFlow, Keras, or scikit‑learn.
Experience working with LLM platforms such as Google Model Garden, Amazon Bedrock, or equivalent cloud‑based AI services.
Strong understanding of NLP, Computer Vision, and vector databases (e.g., Pinecone, Weaviate).
Proficiency in prompt engineering techniques, including zero‑shot, few‑shot, and Chain‑of‑Thought prompting.
Deep knowledge of data science methodologies and sampling strategies for deriving insights and building representative datasets.

Responsibilities

Design, fine‑tune, and optimize advanced AI/ML algorithms, including Generative AI, LLMs, and traditional machine learning models.
Derive data‑driven insights using supervised, unsupervised, reinforcement learning, and deep learning techniques.
Build scalable, secure, end‑to‑end ML pipelines for data ingestion, model training, evaluation, and real‑time inference.
Automate model deployment, monitoring, and drift detection across cloud platforms such as AWS, Azure, or Google Cloud.
Integrate processed datasets with generative AI models to support real‑world business use cases.
Provide technical leadership and mentorship to engineers working on Python development, model integration, and data sampling.
Collaborate with cross‑functional teams including Product, Engineering, and Data Science to shape AI strategy and solution design.
Stay current with emerging AI technologies and implement innovations such as Retrieval‑Augmented Generation (RAG) and Agentic AI.
Ensure best practices in model governance, documentation, and reproducibility.