AI/ML Engineer

Jobgether

10h•Remote

About The Position

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an AI/ML Engineer in United States. This role offers a hands-on opportunity to design, build, and deploy cutting-edge AI and machine learning solutions in high-impact environments. You will develop end-to-end pipelines, optimize models, and integrate AI capabilities into operational systems that directly influence mission-critical outcomes. The position is ideal for engineers who thrive in code, enjoy building production-ready systems, and are excited by complex, real-world challenges. You will collaborate with cross-functional teams to ensure models are reliable, reproducible, and aligned with technical and operational objectives. This role emphasizes both innovation and execution, providing a platform to work on large-scale AI initiatives with tangible, measurable impact.

Requirements

U.S. citizenship with the ability to obtain and maintain a security clearance if required
6â10+ years of professional experience developing and deploying AI/ML solutions in production
Strong Python programming skills with experience in AI/ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or LangChain
Experience building and deploying MLOps pipelines (MLflow, Kubeflow, DVC, or equivalent)
Knowledge of vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval-based architectures (RAG, hybrid, graph)
Experience fine-tuning and evaluating LLMs or task-specific models using LoRA, QLoRA, or PEFT
Proven ability to integrate AI solutions into operational or mission-critical systems
Excellent problem-solving skills, attention to detail, and ability to work collaboratively in high-stakes environments
Bachelorâs or Masterâs degree in Computer Science, Engineering, Data Science, or a related technical field

Nice To Haves

Familiarity with agentic frameworks such as LangGraph, AutoGen, CrewAI, or DSPy
Understanding of prompt engineering, grounding methods, and retrieval quality
Exposure to GPU-based or edge inference environments
Active Secret clearance preferred

Responsibilities

Design, develop, and deploy AI/ML models and pipelines to meet performance and operational objectives
Build, train, and fine-tune models using frameworks like PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain
Develop and operationalize MLOps pipelines with tools such as MLflow, Kubeflow, DVC, or custom orchestration solutions
Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid)
Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services
Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT)
Integrate AI capabilities into production systems via APIs, event-driven workflows, or UI copilots
Collaborate with data engineers, software developers, and analysts to ensure models are production-ready
Participate in peer reviews, document experiments, and contribute to shared repositories for reproducibility